Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial

PURPOSE

Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need.

EXPERIMENTAL DESIGN

Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink.

RESULTS

Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression.

CONCLUSIONS

The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

Growth kinetics of Bacillus cytotoxicus in liquid Egg yolk during treatment with phospholipase A2 - A one-step global dynamic analysis

During commercial production of liquid egg yolk (LEY), phospholipase A2 (PLA2) is used to improve its emulsification capacity and thermal stability. The enzymatic treatment may occur at elevated temperatures such as 50 °C, potentially allowing foodborne pathogens, such as Bacillus cereus, to grow. Little knowledge is available concerning growth of B. cereus in LEY during PLA2 treatment. Therefore, the objective of this study was to investigate the growth kinetics of B. cereus during PLA2 treatment using pathogenic B. cytotoxicus NVH391-98, the most thermotolerant member in the B. cereus group, as a surrogate. Inoculated LEY samples were placed in precision programmable incubators to observe the growth of B. cytotoxicus NVH391-98 under multiple isothermal and dynamic temperature conditions between 20 and 53 °C. The bacterial growth was described using the differential Baranyi model coupled with two different secondary models. The kinetic parameters were determined using one-step dynamic inverse analysis of multiple growth curves. The least square method was used in combination with the 4th order Runge-Kutta method to solve the differential Baranyi model using multiple growth curves to determine the cardinal kinetic parameters. The results showed that B. cytotoxicus NVH391-98 can grow prolifically at 50 °C. The estimated minimum, optimum and maximum temperatures were 16.7 or 18.5, 47.8 or 48.1, and 52.1 or 52.4 °C, respectively, depending on the secondary models, with an optimum growth rate of 2.1 log colony-forming-unit (CFU)/g per hour. The dynamic model is validated using isothermal curves with reasonable accuracy. B. cytotoxicus died off slowly at 15 °C. At 55 °C, thermal inactivation was observed, with a D value of approximately 2.7 h. Holding at 55 °C or below 15 °C can effectively prevent the growth of B. cytotoxicus in egg yolk.

Innovative cellular therapies for autoimmune diseases: expert-based position statement and clinical practice recommendations from the EBMT practice harmonization and guidelines committee

Autoimmune diseases (ADs) are characterized by loss of immune tolerance, high chronicity, with substantial morbidity and mortality, despite conventional immunosuppression (IS) or targeted disease modifying therapies (DMTs), which usually require repeated administration. Recently, novel cellular therapies (CT), including mesenchymal stromal cells (MSC), Chimeric Antigen Receptors T cells (CART) and regulatory T cells (Tregs), have been successfully adopted in ADs. An international expert panel of the European Society for Blood and Marrow Transplantation and the International Society for the Cell and Gene Therapy, reviewed all available evidence, based on the current literature and expert practices, on use of MSC, CART and Tregs, in AD patients with rheumatological, neurological, and gastroenterological indications. Expert-based consensus and recommendations for best practice and quality of patient care were developed to support clinicians, scientists, and their multidisciplinary teams, as well as patients and care providers and will be regularly updated.

Identifying Oncology Clinical Trial Candidates Using Artificial Intelligence Predictions of Treatment Change: A Pilot Implementation Study

PURPOSE

Precision oncology clinical trials often struggle to accrue, partly because it is difficult to find potentially eligible patients at moments when they need new treatment. We piloted deployment of artificial intelligence tools to identify such patients at a large academic cancer center.

PATIENTS AND METHODS

Neural networks that process radiology reports to identify patients likely to start new systemic therapy were applied prospectively for patients with solid tumors that had undergone next-generation sequencing at our center. Model output was linked to the MatchMiner tool, which matches patients to trials using tumor genomics. Reports listing genomically matched patients, sorted by probability of treatment change, were provided weekly to an oncology nurse navigator (ONN) coordinating recruitment to nine early-phase trials. The ONN contacted treating oncologists when patients likely to change treatment appeared potentially trial-eligible.

RESULTS

Within weekly reports to the ONN, 60,199 patient-trial matches were generated for 2,150 patients on the basis of genomics alone. Of these, 3,168 patient-trial matches (5%) corresponding to 525 patients were flagged for ONN review by our model, representing a 95% reduction in review compared with manual review of all patient-trial matches weekly. After ONN review for potential eligibility, treating oncologists for 74 patients were contacted. Common reasons for not contacting treating oncologists included cases where patients had already decided to continue current treatment (21%); the trial had no slots (14%); or the patient was ineligible on ONN review (12%). Of 74 patients whose oncologists were contacted, 10 (14%) had a consult regarding a trial and five (7%) enrolled.

CONCLUSION

This approach facilitated identification of potential patients for clinical trials in real time, but further work to improve accrual must address the many other barriers to trial enrollment in precision oncology research.

Immune determinants of CAR-T cell expansion in solid tumor patients receiving GD2 CAR-T cell therapy

Chimeric antigen receptor T cells (CAR-Ts) have remarkable efficacy in liquid tumors, but limited responses in solid tumors. We conducted a Phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.iC9), demonstrating feasibility and safety of administration in children and young adults with osteosarcoma and neuroblastoma. Since CAR-T efficacy requires adequate CAR-T expansion, patients were grouped into good or poor expanders across dose levels. Patient samples were evaluated by multi-dimensional proteomic, transcriptomic, and epigenetic analyses. T cell assessments identified naive T cells in pre-treatment apheresis associated with good expansion, and exhausted T cells in CAR-T products with poor expansion. Myeloid cell assessment identified CXCR3+ monocytes in pre-treatment apheresis associated with good expansion. Longitudinal analysis of post-treatment samples identified increased CXCR3- classical monocytes in all groups as CAR-T numbers waned. Together, our data uncover mediators of CAR-T biology and correlates of expansion that could be utilized to advance immunotherapies for solid tumor patients.

Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal

International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include (i) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes; (ii) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment; and (iii) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer.

SIGNIFICANCE

Enhanced cBioPortal features allow clinicians and researchers to effectively investigate longitudinal clinico-genomic data from patients with cancer, which will improve exploration of data from the AACR Project GENIE Biopharma Collaborative and similar datasets.

Impact of Aneuploidy and Chromosome 9p Loss on Tumor Immune Microenvironment and Immune Checkpoint Inhibitor Efficacy in NSCLC

INTRODUCTION

Although gene-level copy number alterations have been studied as a potential biomarker of immunotherapy efficacy in NSCLC, the impact of aneuploidy burden and chromosomal arm-level events on immune checkpoint inhibitor (ICI) efficacy in NSCLC is uncertain.

METHODS

Patients who received programmed cell death protein 1 or programmed death-ligand 1 (PD-L1) inhibitor at two academic centers were included. Across all 22 chromosomes analyzed, an arm was considered altered if at least 70% of its territory was either gained or deleted. Among nonsquamous NSCLCs which underwent targeted next-generation sequencing, we retrospectively quantified aneuploidy using the adjusted fraction of chromosomal arm alterations (FAA), defined as the number of altered chromosome arms divided by the number of chromosome arms assessed, adjusted for tumor purity.

RESULTS

Among 2293 nonsquamous NSCLCs identified, the median FAA increased with more advanced cancer stage and decreased with higher PD-L1 tumor proportion score (TPS) levels (median FAA in TPS < 1%: 0.09, TPS 1%-49%: 0.08, TPS ≥ 50%: 0.05, p < 0.0001). There was a very weak correlation between FAA and tumor mutational burden when taken as continuous variables (R: 0.07, p = 0.0005). A total of 765 advanced nonsquamous NSCLCs with available FAA values were treated with ICIs. With decreasing FAA tertiles, there was a progressive improvement in objective response rate (ORR 15.1% in upper tertile versus 23.2% in middle tertile versus 28.4% in lowest tertile, p = 0.001), median progression-free survival (mPFS 2.5 versus 3.3 versus 4.1 mo, p < 0.0001), and median overall survival (mOS 12.5 versus 13.9 versus 16.4 mo, p = 0.006), respectively. In the arm-level enrichment analysis, chromosome 9p loss (OR = 0.22, Q = 0.0002) and chromosome 1q gain (OR = 0.43, Q = 0.002) were significantly enriched in ICI nonresponders after false discovery rate adjustment. Compared with NSCLCs without chromosome 9p loss (n = 452), those with 9p loss (n = 154) had a lower ORR (28.1% versus 7.8%, p < 0.0001), a shorter mPFS (4.1 versus 2.3 mo, p < 0.0001), and a shorter mOS (18.0 versus 9.6 mo, p < 0.0001) to immunotherapy. In addition, among NSCLCs with high PD-L1 expression (TPS ≥ 50%), chromosome 9p loss was associated with lower ORR (43% versus 6%, p < 0.0001), shorter mPFS (6.4 versus 2.6 mo, p = 0.0006), and shorter mOS (30.2 versus 14.3 mo, p = 0.0008) to immunotherapy compared with NSCLCs without 9p loss. In multivariable analysis, adjusting for key variables including FAA, chromosome 9p loss, but not 1q gain, retained a significant impact on ORR (hazard ratio [HR] = 0.25, p < 0.001), mPFS (HR = 1.49, p = 0.001), and mOS (HR = 1.47, p = 0.003). Multiplexed immunofluorescence and computational deconvolution of RNA sequencing data revealed that tumors with either high FAA levels or chromosome 9p loss had significantly fewer tumor-associated cytotoxic immune cells.

CONCLUSIONS

Nonsquamous NSCLCs with high aneuploidy and chromosome 9p loss have a distinct tumor immune microenvironment and less favorable outcomes to ICIs.

Clinicopathologic, Genomic, and Immunophenotypic Landscape of ATM Mutations in Non-Small Cell Lung Cancer

PURPOSE

ATM is the most commonly mutated DNA damage and repair gene in non-small cell lung cancer (NSCLC); however, limited characterization has been pursued.

EXPERIMENTAL DESIGN

Clinicopathologic, genomic, and treatment data were collected for 5,172 patients with NSCLC tumors which underwent genomic profiling. ATM IHC was performed on 182 NSCLCs with ATM mutations. Multiplexed immunofluorescence was performed on a subset of 535 samples to examine tumor-infiltrating immune cell subsets.

RESULTS

A total of 562 deleterious ATM mutations were identified in 9.7% of NSCLC samples. ATM-mutant (ATMMUT) NSCLC was significantly associated with female sex (P = 0.02), ever smoking status (P < 0.001), non-squamous histology (P = 0.004), and higher tumor mutational burden (DFCI, P < 0.0001; MSK, P < 0.0001) compared with ATM-wild-type (ATMWT) cases. Among 3,687 NSCLCs with comprehensive genomic profiling, co-occurring KRAS, STK11, and ARID2 oncogenic mutations were significantly enriched among ATMMUT NSCLCs (Q < 0.05), while TP53 and EGFR mutations were enriched in ATMWT NSCLCs. Among 182 ATMMUT samples with ATM IHC, tumors with nonsense, insertions/deletions, or splice site mutations were significantly more likely to display ATM loss by IHC (71.4% vs. 28.6%; P < 0.0001) compared with tumors with only predicted pathogenic missense mutations. Clinical outcomes to PD-(L)1 monotherapy (N = 1,522) and chemo-immunotherapy (N = 951) were similar between ATMMUT and ATMWT NSCLCs. Patients with concurrent ATM/TP53 mutations had significantly improved response rate and progression-free survival with PD-(L)1 monotherapy.

CONCLUSIONS

Deleterious ATM mutations defined a subset of NSCLC with unique clinicopathologic, genomic, and immunophenotypic features. Our data may serve as resource to guide interpretation of specific ATM mutations in NSCLC.

Abstract 5706: ImmunoPROFILE: A prospective implementation of clinically validated, quantitative immune cell profiling test identifies tumor-infiltrating CD8+ and PD-1+ cell densities as prognostic biomarkers across a 2,023 patient pan-cancer cohort treated with different therapies

Tumor-infiltrating lymphocyte (TIL) density has been identified as a prognostic and predictive biomarker in select tumors treated with defined therapies. These observations suggest that TILs may be general markers of patient outcomes, but evidence in support of this hypothesis has been limited by small cohorts.

We validated ImmunoPROFILE, a multiplexed immunofluorescence (MIF)-based assay coupled with machine-learning-based image analysis, to identify and quantify tumor cells (cytokeratin, PAX5, PAX8, SOX10), T cells (CD8), T-regulatory cells (FOXP3), exhausted cells (PD-1) and immunosuppressive tumor and immune cells (PD-L1). We applied the MIF panel to specimens from patients collected prospectively over three years and analyzed 2,023 cases across 27 tumor types. The association between biomarkers and overall survival (OS) was investigated using Cox models controlling for patient risk factors such as cancer type, metastatic vs. primary disease, age, and gender. Multivariable biomarker selection was based on likelihood ratios.

The assay was highly robust (success rate 97%), reproducible (inter-scanning and intra-staining density controls within 1 SD, inter-staining PD-L1 scores ≤11% CV), and operator-independent (R2 &gt;0.7 to &gt;0.9 for each biomarker and 95% concordance in PD-L1 score-based interpretation between technicians). From whole slide images, a total of 11,932 individual regions of interest were analyzed across the cohort, resulting in &gt;50 million spatially-resolved single cells which were summarized into cell population densities and PD-L1 scores.

High densities of CD8+ (&gt;64/mm2, p&lt;0.0001), PD-1+ (&gt;50/mm2, p&lt;0.0001), and FOXP3+ (&gt;30/mm2, p&lt;0.0001) T cells were associated with longer overall survival (OS) irrespective of therapy and across all cancer types. PD-L1 metrics were not associated with OS (p=0.43). Compared to patients with low densities of CD8+ and PD-1+ cells, high densities of at least one of these cell types had better OS (Both high, HR: 0.49, 95% CI: 0.41 - 0.59; CD8+ high, HR: 0.63, (0.48 - 0.82); PD-1+ high, HR: 0.71, (0.54 - 0.93)). The results were consistent in the subset of patients (N=1572) who did not receive immunotherapy (IO). In patients who received IO therapy (N=451), only PD-1+ T-cell density associated with OS (HR: 0.48, (0.36 - 0.65)).

To our knowledge, this is the first enterprise-level immune biomarker assay using multiplexed staining, digital imaging, and machine learning to be applied in a prospective manner to clinical specimens at scale. We found that select immune cell densities are prognostic across cancer types and therapies and demonstrated that quantification of multiple cell populations yields better prognostic power than single marker analyses.

Citation Format: James Lindsay, Bijaya Sharma, Kristen D. Felt, Anita Giobbie-Hurder, Ian Dryg, Jason L. Weirather, Jennifer Altreuter, Tali Mazor, Priti Kumari, Joao V. Alessi, Ajit J. Nirmal, Michael P. Manos, Ananth R. Kumar, William Lotter, Ethan Cerami, Burce E. Johnson, Neil I. Lindeman, Lynette M. Sholl, Jonathan A. Nowak, Scott J. Rodig. ImmunoPROFILE: A prospective implementation of clinically validated, quantitative immune cell profiling test identifies tumor-infiltrating CD8+ and PD-1+ cell densities as prognostic biomarkers across a 2,023 patient pan-cancer cohort treated with different therapies. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5706.

Abstract 2142: Immune determinants of CAR-T expansion in solid tumor patients receiving GD2 CAR-T cell therapy

Chimeric antigen receptor T cells (CAR-Ts) have demonstrated remarkable efficacy in leukemia and lymphomas but limited responses in solid tumors. We conducted a phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.ICD9), demonstrating feasibility and safety of administering GD2 CAR-Ts in children and young adults with neuroblastoma and, for the first time, osteosarcoma. 15 patients aged 8-28 years were enrolled on four dose levels, of which 13 patients were infused. No dose-limiting toxicities were observed, and administration of up to 1x107 GD2-CAR-T/kg was feasible and safe for children and young adults with neuroblastoma and osteosarcoma. At Day 28 following GD2 CAR-T infusion, 23.1% (3/13) of evaluable patients had progressive disease and 76.9% (10/13) had stable disease (SD). 3/10 SD patients remained stable at 60 days post-infusion of GD2 CAR-T, but all patients eventually progressed. Since a major barrier to CAR-T efficacy is inadequate CAR-T expansion, we evaluated CAR-T levels and found that patients stratified into good and poor expander groups, observed across dose levels and associated with pro-inflammatory cytokine signatures in patients. To understand the immune cell contributors to CAR-T expansion, patient pre-treatment apheresis, CAR-T product, and post-infusion samples were evaluated by high-dimensional proteomic (CyTOF), transcriptomic (RNAseq), and epigenetic (ATACseq) analyses. In patient apheresis, good CAR-T expansion associated with more open chromatin and with both proteomic and transcriptomic enrichment of naïve T cells, while poor CAR-T expansion associated with increased levels of T effector memory (TEMRA) cells and enrichment of myeloid derived suppressor cell (MDSC) transcriptomic signatures. CAR-T products across patients, regardless of CAR-T expansion, demonstrated increased T cell activation proteomic signatures, with enhanced exhaustion transcriptomic signatures in poor expanders compared to good. The most robust cellular correlate to good CAR-T expansion was a population of CXCR3-expressing monocytes in pre-treatment apheresis. Interestingly, this CXCR3+ monocyte population reduced in post-infusion timepoints of good expanders, resembling levels found in poor expanders. Our findings were validated in TARGET-OS patient data in The Cancer Genome Atlas, where high CXCR3 expression was found to be associated with survival benefit in osteosarcoma patients. CXCR3 has been extensively studied on T cells, but its function on myeloid populations is yet to be fully explored. These results are the first to demonstrate that the peripheral immune environment prior to CAR-T administration may effectively predict and modulate CAR-T expansion in patients.

Citation Format: Tara Murty, Sabina Kaczanowska, Ahmad Alimadadi, Cristina Contreras, Caroline Duault, Priyanka Balasubrahmanyan, Warren Reynolds, Norma Gutierrez, Reema Baskar, Catherine Wu, Franziska Michor, Jennifer Altreuter, Yang Liu, Aashna Jhaveri, Vandon Duong, Hima Anbunathan, Radim Moravec, Joyce Hong, Roshni Biswas, Stephen Van Nostrand, James Lindsay, Mina Pichavant, Elena Sotillo, Bita Sahaf, Sean Bendall, Holden Maecker, Steven Highfill, David Stroncek, Melinda Merchant, John Glod, Catherine Hedrick, Crystal Mackall, Sneha Ramakrishna, Rosandra Kaplan. Immune determinants of CAR-T expansion in solid tumor patients receiving GD2 CAR-T cell therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2142.

Abstract 4256: cBioPortal for Cancer Genomics

cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale clinico-genomic data sets. cBioPortal provides a suite of user-friendly visualizations and analyses, including OncoPrints, mutation “lollipop” plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization.

The public site (https://www.cbioportal.org) is accessed by &gt;35,000 unique visitors each month and hosts data from &gt;350 studies spanning individual labs and large consortia. In addition, at least 74 instances of cBioPortal are installed at academic institutions and companies worldwide. To better support all users, we unified our documentation (https://docs.cbioportal.org) and added a user guide and an ongoing series of ‘how-to’ videos to address common questions.

In 2022 we added 32 studies (&gt;38,000 samples) to the public site. In addition, we added a nonsynonymous tumor mutation burden (TMB) value for all samples and enhanced the TCGA PanCancer Atlas studies with DNA methylation and treatment data. All data is available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub.

We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of &gt;165,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). The GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations, including response, outcome, and treatment history. The first BPC cohorts are now available: ~2,000 non-small cell lung cancer samples and ~1,500 colorectal cancer samples.

Support for multimodal data analysis has been a major focus, including several new integrations with external tools. Single cell data is now available in the CPTAC GBM study and can be visualized throughout cBioPortal, and via integration with cellxgene. On the patient page, H&E and mIF images can be visualized via integration with Minerva, and the genomic overview now integrates IGV.

We continue to enhance existing features. In the study view, users can now add charts comparing categorical vs continuous data, and the plots tab includes a heatmap option. We replaced the existing fusion data type with a generalized structural variant data type that supports detailed information including breakpoints and orientation, to enable new visualizations and analyses. Pathway level analysis has been extended with a new integration with NDEx.

cBioPortal is fully open source (https://github.com/cBioPortal/). Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, Caris Life Sciences, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community.

Citation Format: Ino de Bruijn, Tali Mazor, Adam Abeshouse, Diana Baiceanu, Stephanie Carrero, Elena Garcia Lara, Benjamin Gross, David M. Higgins, Prasanna K. Jagannathan, Priti Kumari, Ritika Kundra, Bryan Lai, Xiang Li, James Lindsay, Aaron Lisman, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Yusuf Ziya Özgül, Oleguer Plantalech, Sander Rodenburg, Baby Anusha Satravada, Robert Sheridan, Lucas Sikina, Jessica Singh, S Onur Sumer, Yichao Sun, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Sjoerd van Hagen, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Jianjiong Gao, Nikolaus Schultz. cBioPortal for Cancer Genomics. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4256.

Clonal KEAP1 mutations with loss of heterozygosity share reduced immunotherapy efficacy and low immune cell infiltration in lung adenocarcinoma

BACKGROUND

KEAP1 mutations have been associated with reduced survival in lung adenocarcinoma (LUAD) patients treated with immune checkpoint inhibitors (ICIs), particularly in the presence of STK11/KRAS alterations. We hypothesized that, beyond co-occurring genomic events, clonality prediction may help identify deleterious KEAP1 mutations and their counterparts with retained sensitivity to ICIs.

PATIENTS AND METHODS

Beta-binomial modelling of sequencing read counts was used to infer KEAP1 clonal inactivation by combined somatic mutation and loss of heterozygosity (KEAP1 C-LOH) versus partial inactivation [KEAP1 clonal diploid-subclonal (KEAP1 CD-SC)] in the Memorial Sloan Kettering Cancer Center (MSK) MetTropism cohort (N = 2550). Clonality/LOH prediction was compared to a streamlined clinical classifier that relies on variant allele frequencies (VAFs) and tumor purity (TP) (VAF/TP ratio). The impact of this classification on survival outcomes was tested in two independent cohorts of LUAD patients treated with immunotherapy (MSK/Rome N = 237; DFCI N = 461). Immune-related features were studied by exploiting RNA-sequencing data (TCGA) and multiplexed immunofluorescence (DFCI mIF cohort).

RESULTS

Clonality/LOH inference in the MSK MetTropism cohort overlapped with a clinical classification model defined by the VAF/TP ratio. In the ICI-treated MSK/Rome discovery cohort, predicted KEAP1 C-LOH mutations were associated with shorter progression-free survival (PFS) and overall survival (OS) compared to KEAP1 wild-type cases (PFS log-rank P = 0.001; OS log-rank P < 0.001). Similar results were obtained in the DFCI validation cohort (PFS log-rank P = 0.006; OS log-rank P = 0.014). In both cohorts, we did not observe any significant difference in survival outcomes when comparing KEAP1 CD-SC and wild-type tumors. Immune deconvolution and multiplexed immunofluorescence revealed that KEAP1 C-LOH and KEAP1 CD-SC differed for immune-related features.

CONCLUSIONS

KEAP1 C-LOH mutations are associated with an immune-excluded phenotype and worse clinical outcomes among advanced LUAD patients treated with ICIs. By contrast, survival outcomes of patients whose tumors harbored KEAP1 CD-SC mutations were similar to those with KEAP1 wild-type LUADs.

Experimental testing of a prototype cantilevered liquid-nitrogen-cooled silicon mirror

This report presents testing of a prototype cantilevered liquid-nitrogen-cooled silicon mirror. This mirror was designed to be the first mirror for the new soft X-ray beamlines to be built as part of the Advanced Light Source Upgrade. Test activities focused on fracture, heat transfer, modal response and distortion, and indicated that the mirror functions as intended.

Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois - First USA case study

Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict mycotoxin contamination of corn in Illinois, a major corn producing state in the USA. Historical monthly meteorological data from a 14-year period combined with corresponding aflatoxin and fumonisin contamination data from the State of Illinois were used to engineer input features that link weather, fungal growth, and aflatoxin production in combination with gradient boosting (GBM) and bayesian network (BN) modeling. The GBM and BN models developed can predict mycotoxin contamination with overall 94% accuracy. Analyses for aflatoxin and fumonisin with GBM showed that meteorological and satellite-acquired vegetative index data during March significantly influenced grain contamination at the end of the corn growing season. Prediction of high aflatoxin contamination levels was linked to high aflatoxin risk index in March/June/July, high vegetative index in March and low vegetative index in July. Correspondingly, high levels of fumonisin contamination were linked to high precipitation levels in February/March/September and high vegetative index in March. During corn flowering time in June, higher temperatures range increased prediction of high levels of fumonisin contamination, while high aflatoxin contamination levels were linked to high aflatoxin risk index. Meteorological events prior to corn planting in the field have high influence on predicting aflatoxin and fumonisin contamination levels at the end of the year. These early-year events detected by the models can directly assist farmers and stakeholders to make informed decisions to prevent mycotoxin contamination of Illinois grown corn.

Genomic analysis of early-stage lung cancer reveals a role for TP53 mutations in distant metastasis

Patients with non-small cell lung cancer (NSCLC) who have distant metastases have a poor prognosis. To determine which genomic factors of the primary tumor are associated with metastasis, we analyzed data from 759 patients originally diagnosed with stage I-III NSCLC as part of the AACR Project GENIE Biopharma Collaborative consortium. We found that TP53 mutations were significantly associated with the development of new distant metastases. TP53 mutations were also more prevalent in patients with a history of smoking, suggesting that these patients may be at increased risk for distant metastasis. Our results suggest that additional investigation of the optimal management of patients with early-stage NSCLC harboring TP53 mutations at diagnosis is warranted in light of their higher likelihood of developing new distant metastases.

MatchMiner: an open-source platform for cancer precision medicine

Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner’s capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner’s primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial’s eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner’s impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.

Dissecting the clinicopathologic, genomic, and immunophenotypic correlates of KRASG12D-mutated non-small-cell lung cancer

BACKGROUND

Allele-specific KRAS inhibitors are an emerging class of cancer therapies. KRAS-mutant (KRASMUT) non-small-cell lung cancers (NSCLCs) exhibit heterogeneous outcomes, driven by differences in underlying biology shaped by co-mutations. In contrast to KRASG12C NSCLC, KRASG12D NSCLC is associated with low/never-smoking status and is largely uncharacterized.

PATIENTS AND METHODS

Clinicopathologic and genomic information were collected from patients with NSCLCs harboring a KRAS mutation at the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center, MD Anderson Cancer Center, and Imperial College of London. Multiplexed immunofluorescence for CK7, programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), Foxp3, and CD8 was carried out on a subset of samples with available tissue at the DFCI. Clinical outcomes to PD-(L)1 inhibition ± chemotherapy were analyzed according to KRAS mutation subtype.

RESULTS

Of 2327 patients with KRAS-mutated (KRASMUT) NSCLC, 15% (n = 354) harbored KRASG12D. Compared to KRASnon-G12D NSCLC, KRASG12D NSCLC had a lower pack-year (py) smoking history (median 22.5 py versus 30.0 py, P < 0.0001) and was enriched in never smokers (22% versus 5%, P < 0.0001). KRASG12D had lower PD-L1 tumor proportion score (TPS) (median 1% versus 5%, P < 0.01) and lower tumor mutation burden (TMB) compared to KRASnon-G12D (median 8.4 versus 9.9 mt/Mb, P < 0.0001). Of the samples which underwent multiplexed immunofluorescence, KRASG12D had lower intratumoral and total CD8+PD1+ T cells (P < 0.05). Among 850 patients with advanced KRASMUT NSCLC who received PD-(L)1-based therapies, KRASG12D was associated with a worse objective response rate (ORR) (15.8% versus 28.4%, P = 0.03), progression-free survival (PFS) [hazard ratio (HR) 1.51, 95% confidence interval (CI) 1.45-2.00, P = 0.003], and overall survival (OS; HR 1.45, 1.05-1.99, P = 0.02) to PD-(L)1 inhibition alone but not to chemo-immunotherapy combinations [ORR 30.6% versus 35.7%, P = 0.51; PFS HR 1.28 (95%CI 0.92-1.77), P = 0.13; OS HR 1.36 (95%CI 0.95-1.96), P = 0.09] compared to KRASnon-G12D.

CONCLUSIONS

KRASG12D lung cancers harbor distinct clinical, genomic, and immunologic features compared to other KRAS-mutated lung cancers and worse outcomes to PD-(L)1 blockade. Drug development for KRASG12D lung cancers will have to take these differences into account.

AACR Project GENIE: 100,000 Cases and Beyond

The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally.

SIGNIFICANCE

AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data. This article is highlighted in the In This Issue feature, p. 2007.

Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels

Importance

Although tumor mutation burden (TMB) has been explored as a potential biomarker of immunotherapy efficacy in solid tumors, there still is a lack of consensus about the optimal TMB threshold that best discriminates improved outcomes of immune checkpoint inhibitor therapy among patients with non-small cell lung cancer (NSCLC).

Objectives

To determine the association between increasing TMB levels and immunotherapy efficacy across clinically relevant programmed death ligand-1 (PD-L1) levels in patients with NSCLC.

Design, Setting, and Participants

This multicenter cohort study included patients with advanced NSCLC treated with immunotherapy who received programmed cell death-1 (PD-1) or PD-L1 inhibition in the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center (MSKCC), and in the Stand Up To Cancer (SU2C)/Mark Foundation data sets. Clinicopathological and genomic data were collected from patients between September 2013 and September 2020. Data analysis was performed from November 2021 to February 2022.

Exposures

Treatment with PD-1/PD-L1 inhibition without chemotherapy.

Main Outcomes and Measures

Association of TMB levels with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).

Results

In the entire cohort of 1552 patients with advanced NSCLC who received PD-1/PD-L1 blockade, the median (range) age was 66 (22-92) years, 830 (53.5%) were women, and 1347 (86.8%) had cancer with nonsquamous histologic profile. A regression tree modeling ORR as a function of TMB identified 2 TMB groupings in the discovery cohort (MSKCC), defined as low TMB (≤19.0 mutations per megabase) and high TMB (>19.0 mutations per megabase), which were associated with increasing improvements in ORR, PFS, and OS in the discovery cohort and in 2 independent cohorts (DFCI and SU2C/Mark Foundation). These TMB levels also were associated with significant improvements in outcomes of immunotherapy in each PD-L1 tumor proportion score subgroup of less than 1%, 1% to 49%, and 50% or higher. The ORR to PD-1/PD-L1 inhibition was as high as 57% in patients with high TMB and PD-L1 expression 50% or higher and as low as 8.7% in patients with low TMB and PD-L1 expression less than 1%. Multiplexed immunofluorescence and transcriptomic profiling revealed that high TMB levels were associated with increased CD8-positive, PD-L1-positive T-cell infiltration, increased PD-L1 expression on tumor and immune cells, and upregulation of innate and adaptive immune response signatures.

Conclusions and Relevance

These findings suggest that increasing TMB levels are associated with immune cell infiltration and an inflammatory T-cell-mediated response, resulting in increased sensitivity to PD-1/PD-L1 blockade in NSCLC across PD-L1 expression subgroups.

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

Abstract 2143: Clinicopathologic, genomic and immunophenotypic landscape of ATM mutations in non-small cell lung cancer

Introduction: Defective DNA damage repair machinery is a hallmark of cancer, resulting in increased mutation rates and genomic instability. In non-small cell lung cancer (NSCLC), ATM is mutated in ~10% of cases, representing the most commonly mutated DNA damage and repair gene. However, the clinicopathologic, genomic, and immunophenotypic correlates of ATM mutations in NSCLC are unknown. The impact of ATM mutation on clinical outcomes to PD-(L)1 blockade is also unclear.

Methods: Clinicopathologic and genomic data were collected from 3592 patients (pts) with NSCLC who had consented to correlative studies at the Dana-Farber Cancer Institute (DFCI), and whose tumors underwent genomic profiling (OncoPanel). Multiplexed immunofluorescence (mIF) for CD8, PD1, PD-L1, FOXP3, and CK AE1/AE3 was performed on a subset of 416 NSCLC samples to examine tumor-infiltrating immune cells. ATM immunohistochemistry (IHC) was also performed on 184 ATM mutated NSCLCs with available tissue. ATM mutated (ATMMUT) tumors were defined as harboring loss-of-function mutations (nonsense, frameshift, splice site, known deleterious missense mutations). Missense mutation of unknown significance were excluded, unless deemed to affect protein function in silico. Tumors lacking ATM mutations or harboring benign ATM alterations were defined as ATM wild type (ATMWT).

Results: A total of 399 deleterious ATM mutations were identified in 10.2% (365/3592) of samples; 138 (34.6%) mutations were truncating (nonsense, frameshift, and splice site mutations); the remaining 261 (65.4%) were missense mutations. Truncating mutations were significantly more likely to result in ATM loss by IHC compared to missense mutations (71.4% vs 28.9%, P&lt;0.01) When we examined the genomic profiles of tumors with versus without deleterious ATM mutations, we found that ATMMUT NSCLCs were significantly enriched with KRAS, STK11, RBM10, and KDM5C co-mutations (P&lt;0.01), while co-mutations in EGFR, CDKN2A and TP53 were nearly mutually exclusive (P&lt;0.01). Among ATMMUT NSCLCs, those with ATM loss by IHC were significantly enriched with KRAS and STK11 co-mutations, while those with retained ATM expression were enriched with TP53 co-mutations (P&lt;0.01). Pts with ATMMUT NSCLCs had similar outcomes to PD-(L)1 inhibition +/- chemotherapy, compared to ATMWT cases, and similar immune cell subsets infiltration (P&gt;0.05). Pts with deleterious mutations in ATM and TP53 (ATMMUT/TP53MUT) had increased response rates to chemo-immunotherapy compared to those with ATMMUT/TP53WT, ATMWT/TP53MUT, or ATMWT/TP53WT genotypes (70% vs 56.2% vs 35.7% vs 27.4%, respectively, P=0.01), as well as increased tumor-stroma interface CD8+ T cells (P&lt;0.01) and higher PD-L1 expression by mIF on tumor (P&lt;0.01) and immune cells (P&lt;0.01).

Conclusion: Deleterious ATM mutations defined a subset of NSCLC with unique clinicopathologic, genomic, and immunophenotypic features.

Citation Format: Biagio Ricciuti, Joao Victor Alessi, Xinan Wang, Arrien A. Bertram, Victor R. Vaz, Mizuki Nishino, James Lindsay, Kristen D. Felt, Bijaya Sharma, Lynette M. Sholl, Rodig Scott, Mark M. Awad, Michael L. Cheng. Clinicopathologic, genomic and immunophenotypic landscape of ATM mutations in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2143.

Abstract 2580: Infiltration and spatial distribution of immune cells are associated clinical benefit from Nivolumab and Ipilimumab for previously treated patients with stage IV squamous cell lung cancer: an immune biomarker analysis of Phase III SWOG LungMAP S1400I trial

Background: Lung squamous cell carcinoma (SCC) is the second most common type of non-small cell lung cancer. Immunotherapy is a promising treatment for SCC. However, only a small proportion of unselected SCC patients are able to achieve durable clinical benefit. We leveraged the precious specimens from S1400I trial and sought to explore whether the levels and spatial distributions of tumor-associated immune cells (TAICs) in screening samples are associated with PFS, and OS.

Methods: We utilized paraffin tumor tissue provided by the SWOG bank from screening on LungMAP. 82/252 eligible SCC sample from patients treated with nivolumab plus ipilimumab (nivo+ipi; n = 35) or with nivolumab alone (nivo; n = 47) were studied. Image analysis tissue immunoprofiling was conducted using 9 markers in 2 multiplex immunofluorescence panels against cytokeratin, CD3, CD8, granzyme B, CD45RO, and FOXP3, PD1, PD-L1, and CD68. Densities of cells phenotypes (cells/mm2) were assessed and dichotomized as being high (&gt; median) or low (≤ median) in tumor, stroma, and total compartments. Distances from malignant cells (MCs) to cell populations were measured and dichotomized as close from MCs (≤ median) and faraway from MCs (&gt; median) and associated with clinical variables. Clinicopathologic features and data on PFS, and OS were retrieved from the CIDC portal as provided by the LungMap team. Non-parametric tests where utilized to assessment associations of cell phenotypes versus continue or categorical variables and log-rank test for survival analysis.

Results: Univariate analysis showed that higher densities of memory T cells in total compartment (HR:0.63, CI:0.40-1.00, P=0.041), antigen-experienced T cells in the stroma (HR:0.60, CI:0.37-0.96, P=0.024) and total compartment (HR:0.60, CI:0.38-0.95, P=0.023) and activated cytotoxic T cells in the tumor compartment (HR:0.55, CI:0.35-0.87, P=0.011) were associated with significative better PFS. In the nivo+ipi arm, higher ratios of cytotoxic T cells to regulatory T cells in the stroma were associated with better PFS. The spatial analysis of these TAICs showed that the presence of activated cytotoxic T cells close to the MCs (median, ≤19.27 µm) was associated with better PFS (P=0.037).

Conclusions: Our findings suggest that patients who have a detectable immunosuppressive tumor axis (PD-L1/PD1) with adequate activated cytotoxic T cells close to the tumor cells are the ideal patients for immune therapy to be targetable with these types of treatments.

Acknowledgments: Scientific and financial support for: U10CA180888, U10CA180819U24CA224285, U24CA224316, PACT, PPP and FNIH.

Citation Format: Edwin Roger Parra, Jiexin Zhang, Mary Redman, Rossana Lazcano, Piubelli Mario, Caddie Laberiano Fernandez, Renganayaki K. Krishna, Shanyu Zhang, Hong Chen, Ganiraju Manyam, Radim Moravec, Ethan Cerami, James Lindsay, Joyce Yu, Roshni Biswas, Stephen Van Nostrand, Dzifa Y. Duose, Jianjun Zhang, Roy Herbst, Gheath Al-Atrash, Kasthuri Kannan, Ignacio I. Wistuba, Scott Gettinger, Lyudmila Bazhenova, Jack Lee, Jianhua Zhang, Cara Haymaker. Infiltration and spatial distribution of immune cells are associated clinical benefit from Nivolumab and Ipilimumab for previously treated patients with stage IV squamous cell lung cancer: an immune biomarker analysis of Phase III SWOG LungMAP S1400I trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2580.

Abstract CT142: GD2.Ox40.CD28.z CAR T cell trial in neuroblastoma and osteosarcoma

Background: Chimeric antigen receptor T cells (CARTs) hold promising therapeutic potential for refractory tumors. GD2 is a tumor antigen expressed on neuroblastoma and osteosarcoma. In initial studies, T cells expressing 1st generation GD2-CARTs were shown to be safe and mediated modest antitumor activity in some patients with refractory neuroblastoma.

Methods: We developed a 3rd generation GD2-CART (GD2-CAR.OX40.28.z.ICD9) and conducted a phase I trial (NCT02107963) to determine the feasibility of producing and safety of administering escalating doses of GD2-CARTs in children and young adults with GD2+ solid tumors, including neuroblastoma and osteosarcoma, following cyclophosphamide-based lymphodepletion. Patient samples were evaluated for cytokine profile kinetics, immune phenotype analysis with mass cytometry (CyTOF), transcriptomic evaluation with RNA-sequencing (RNA-seq), epigenetic determination with Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), and functional studies with flow cytometry.

Results: 15 patients aged 8-28 years were enrolled on four dose levels, of which 13 patients were infused. No dose-limiting toxicities were observed and administration of up to 1x107 GD2-CART/kg was feasible and safe for children and young adults with neuroblastoma and osteosarcoma. 15.4% (2/13) of patients experienced grade-1 cytokine release syndrome (CRS) and no neurological toxicity was observed. We measured the expansion and persistence of adoptively transferred GD2-CARTs in the peripheral blood. GD2-CARTs expanded in all patients receiving treatment, half of whom had expansion similar to that seen in clinically active CD19 and CD22 CARTs, but the GD2-CARTs had limited persistence. At Day 28 following GD2-CART infusion, 23.1% (3/13) of evaluable patients had progressive disease and 76.9% (10/13) had stable disease (SD). 3/10 SD patients remained stable at 60 days post-GD2-CART, but all patients eventually progressed. Since a major barrier to CART efficacy is inadequate CART expansion, we comprehensively evaluated for phenotypic, transcriptomic, and epigenetic immune profiles of patient apheresis, CART product, and post-treatment peripheral blood samples to identify determinants of CART expansion. GD2-CART expansion is significantly correlated with several T cell markers, and a larger baseline naïve and central memory T cell pool. Unique myeloid populations are associated with CART expansion. ATACseq identifies epigenetic differences in pre-treatment apheresis that may predict good CAR expansion in patients.

Conclusions: GD2-CART therapy following cyclophosphamide conditioning was well tolerated at all four dose levels in pediatric and young adult patients with neuroblastoma and osteosarcoma. Subsequent multi-dimensional analyses suggest key mechanisms underlying CART biology and function and highlight the potential of defining and applying molecular signatures in apheresis and CART product as biomarkers and prognostic indicators of CART expansion, with promise for advancing immunotherapies for solid tumor patients in the future.

Citation Format: Sneha Ramakrishna, Sabina Kaczanowska, Tara Murty, Cristina F. Contreras, Melinda Merchant, John Glod, Norma Gutierrez, Ahmad Alimadadi, David Stroncek, Steven Highfill, Caroline Duault, Priyanka B. Subrahmanyam, Tyson Holmes, Warren Reynolds, Reema Baskar, Antoine Barge, Hayley Lyon, Radim Moravec, Srinika Ranasinghe, Joyce Yu, Roshni Biswas, Samuel Pollack, Stephen Van Nostrand, James Lindsay, Mina Pichavant, Bita Sahaf, Sean C. Bendall, Andrew J. Gentles, Holden Maecker, Catherine C. Hedrick, Crystal Mackall, Rosandra Kaplan. GD2.Ox40.CD28.z CAR T cell trial in neuroblastoma and osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT142.

Abstract 5026: Dynamic changes in circulating protein levels reveal an association between ipilimumab and nivolumab combination treatment (SWOG Lung-MAP S1400I trial) with outcomes in squamous cell lung cancer

Squamous cell lung cancer (SqCLC) is a type of non-small cell lung cancer strongly associated with cigarette smoking and with known targetable mutations, however some patients do not have matching targeted drugs. The S1400I Phase III randomized LungMap sub-study of nivo+ipi versus nivo accrued 275 (252 eligible) previously-treated patients with stage IV SqCLC and absence of matched mutations (NCT02154490).Here, to investigate the longitudinal (baseline, C2 week 3, C4 week 7, C5 week 9) serum protein changes associated with treatment or response, we performed Olink proximity extension assay in 160 patients (561 samples) using an immuno-oncology panel of 92 analytes. We utilized mixed linear and joint models to identify differentially expressed proteins between treatment arms (nivo vs. nivo+ipi), response and quantify the effect of other potential prognostic factors. This approach quantifies the effect of covariates such as smoking status, demographics, prior radiation therapy, and metastases. We jointly modeled expression and survival to identify changes in proteins over time. The thresholds for significance in differentially expression tests were a log fold change of at least 0.5 and a false discovery rate of under 0.05 (FDR as a multiple testing adjustment method). The joint models used thresholds of log fold change of more than 1 and hazard ratio of more than 1. Results revealed increases in 40 serum proteins after treatment with either nivo alone or combined with ipi, including CXCL9, CXCL10, CXCL11, CXCL13, IL6, IL8, IL10, IFNg, and soluble PD-L1 and PDCD1. nivo+ipi treatment showed greater increases in IL8 and CXCL13 post-treatment compared to nivo alone. In addition, circulating IL6, CXCL13, and MIC-A/B were higher in patients with stable or progressive disease compared to those with objective response after treatment. The joint model revealed a worse hazard ratio with increases in 10 soluble proteins, including IL6, IL8, and CXCL13. Finally, for patients with similar values of IL8, those treated by combination had a better survival outcome than those treated by nivo alone. Using a data-modeling approach, we identified significant longitudinal changes in 40 serum proteins out of 92 tested in patients with SqCLC treated with nivo or nivo+ipi. Increases in serum inflammatory markers IL6 and CXCL13 were associated with worse disease. Although overall survival was not statistically different between arms, our modeling approaches suggested that IL-8 monitoring may help identify patients benefiting more from the combination vs. nivo alone.

Citation Format: Edgar Gonzalez-Kozlova, Hsin-Hui Huang, Mary Redman, Roy Herbst, Scott Gettinger, Luda Bazhenova, Hui Xie, Manishkumar Patel, Kai Nie, Jocelyn Harris, Kimberly Argueta, Karen Kelly, Ethan Cerami, James Lindsay, Joyce Yu, Roshni Biswas, Stephen Van Nostrand, Radim Moravec, Diane Marie Del Valle, Seunghee Kim-schulze, Sacha Gnjatic. Dynamic changes in circulating protein levels reveal an association between ipilimumab and nivolumab combination treatment (SWOG Lung-MAP S1400I trial) with outcomes in squamous cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5026.

Abstract 1155: cBioPortal for cancer genomics

cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale cancer genomics data sets. cBioPortal provides a user-friendly interface that integrates genomic and clinical data, and provides a suite of visualizations and analyses, including OncoPrints, mutation “lollipop” plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization. cBioPortal also integrates external tools including CIViC, Cancer Digital Slide Archive, Next-Generation Clustered Heat Map, IGV and Bioconductor to facilitate interpretation.

The public site (https://www.cbioportal.org) is accessed by ~35,000 unique visitors each month and hosts data from &gt;325 studies spanning individual labs and large consortia. In addition, &gt;67 instances of cBioPortal are installed at academic institutions and pharmaceutical/biotechnology companies worldwide. In 2021 we added data from 32 studies, totaling &gt;24,000 samples, to the public site. All data is also available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub/.

We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of &gt;135,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). In addition, the GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations, including response, outcome, and treatment histories. The first BPC release contains data from &gt;1,800 non-small cell lung cancer samples and will be released in early 2022.

The growing GENIE cohort and the BPC clinical data have driven a number of recent developments, including performance improvements (the load time for the GENIE cohort was reduced from minutes to seconds). To leverage the BPC clinical data, we enabled sample selection based on treatment status, extended support for outcome analysis, and enhanced the patient timeline representation to incorporate response data.

Additional development work has focused on improvements to variant interpretation, enhancements to the Mutations tab, and support for novel molecular assays via the ‘generic assay’ data type. Documentation on these new features and many others is available at https://www.cbioportal.org/news.

cBioPortal is fully open source (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community.

Citation Format: Jianjiong Gao, Tali Mazor, Ino de Bruijn, Adam Abeshouse, Diana Baiceanu, Ziya Erkoc, Elena Garcia Lara, Benjamin Gross, David M. Higgins, Prasanna K. Jagannathan, Priti Kumari, Ritika Kundra, Xiang Li, James Lindsay, Aaron Lisman, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Sander Rodenburg, Baby A. Satravada, Robert Sheridan, Lucas Sikina, Jessica Singh, S. Onur Sumer, Yichao Sun, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Sjoerd van Hagen, Kees van Bochove, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. cBioPortal for cancer genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1155.

Abstract 4117: Clinicopathologic and molecular characterization of KRASG12D lung cancers

Introduction: Allele-specific KRAS inhibitors are an emerging class of cancer therapies. KRASmut non-small cell lung cancers (NSCLCs) exhibit heterogenous outcomes, driven by differences in underlying biology shaped by co-mutations. In contrast to KRASG12C NSCLC, KRASG12D NSCLC is associated with low/never smoking status and has not been characterized in depth.

Methods: We examined characteristics of patients with advanced KRASmut NSCLC seen at a single center. RECISTv1.1 and Cox-proportional hazards models adjusting for line of therapy and performance status were used to compare outcomes to immunotherapy. Benjamini-Hochberg corrected q-values were used for genomic comparisons.

Results: Of 1,823 patients with KRASmut NSCLC, 16% (n=283) harbored KRASG12D which was mutually exclusive from other targetable alterations. Among these, the median age was 66 (range 20-92), 0.7% had squamous histology, 30% had a never/light smoking history (&lt;10 pack-years, KRASG12D,light-sm) and 43% had a high pack-year smoking history (≥30 pack-years, KRASG12D,high-sm). Compared to KRASnon-G12D NSCLC, KRASG12D NSCLC had a lower pack-year smoking history (median 22 vs 30, p&lt;0.0001), more commonly had NKX2-1 and CDKN2A co-mutations (q&lt;0.05), and less commonly had STK11 co-mutations (q&lt;0.05). KRASG12D had lower PD-L1 tumor proportion score (TPS) (median 1% vs 10%, p=0.01) and lower tumor mutation burden (TMB) compared to KRASnon-G12D (median 8.3 v 9.9 mt/Mb, p&lt;0.0001). Compared with KRASG12D,high-sm, KRASG12D,light-sm had lower PD-L1 TPS (median 0% vs 10%, p=0.005) and TMB (median 6.1 vs 9.9 mt/Mb, p&lt;0.0001).As compared to patients with KRASnon-G12D (n=120) NSCLC and adequate baseline tissue for multiplex-immunofluorescence, KRASG12D (n=25) had fewer CD8+PD1+ T cells (median 13 vs 32 cells/mm2, p=0.04), PD1+ T cells (median 90 vs 135 cells/mm2, p=0.03), and lower proportion of PD-L1+ tumor and immune cells (median 1.2% vs 3.3%, p=0.06 and median 3.4% vs 7.5%, p=0.01, respectively).Among the subset of patients with advanced KRASmut NSCLC who received immunotherapy (n=57 with KRASG12D, n=411 with KRASnon-G12D), there was no difference in clinical outcomes to anti-PD-(L)1 monotherapy between KRASG12D and KRASnon-G12D (ORR: 18% vs 26%, p=0.3; mPFS: 2.8 vs 3.9 months, aHR 0.86 95% CI 0.60-1.25; mOS: 7.4 vs 15.1 months, aHR 0.77 95% CI 0.51-1.16). Similarly, there was no difference in clinical outcomes to chemo-immunotherapy between KRASG12D and KRASnon-G12D (ORR: 18% vs 39%, p=0.10; mPFS: 6.3 vs 7.0 months, aHR 0.79 95% CI 0.43-1.43; mOS: 14.0 vs 20.8 months, aHR 0.72 95% CI 0.38-1.35).

Conclusions: KRASG12D lung cancers harbor distinct clinical, genomic, and immunologic features compared to other KRAS mutated lung cancers and numerically worse outcomes to PD-(L)1 blockade-based therapies. Drug development for KRASG12D lung cancers will have to take these differences into account.

Citation Format: Jia Luo, Biagio Ricciuti, Joao V. Alessi, Xinan Wang, Victor Vaz, Federica Pecci, Tom Nguyen, James Lindsay, Bijaya Sharma, Kristen D. Felt, Scott J. Rodig, Mizuki H. Nishino, Lynette M. Sholl, David A. Barbie, Pasi A. Jänne, Mark M. Awad. Clinicopathologic and molecular characterization of KRASG12D lung cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4117.

Abstract 4091: Design and adoption of MatchMiner at Dana-Farber Cancer Institute

Precision medicine (PM) drugs targeting alterations such as EGFR mutations and BCR-ABL fusions have provided great clinical benefit to patients. However, with an abundance of tumor sequencing data and trial eligibility criteria available, it can be challenging for clinicians to identify PM trial options for patients. To address this challenge at Dana-Farber Cancer Institute (DFCI), we developed MatchMiner, an open-source platform for computationally matching patients to PM trials. MatchMiner has three modes of use: (1) patient-centric, where clinicians can view all available trial matches for a patient, (2) trial-centric, where clinical trial teams identify patients for their trials based on genomic and clinical criteria, and (3) trial search, where clinicians search for available trials based on clinical and genomic eligibility. Trial matching is performed via the MatchEngine, which computes trial matches based on patient genomic and clinical data and PM trial eligibility criteria. To encode trial eligibility criteria, we developed a structured format called clinical trial markup language (CTML), which uses Boolean logic to encode inclusion and exclusion criteria. Here, we describe our implementation of MatchMiner at DFCI including strategies that were successful and MatchMiner’s impact on trial consent. Since MatchMiner first went live in March 2017, a number of strategies have helped facilitate utilization of MatchMiner. The biggest impact has come from targeted departmental collaborations (Gastrointestinal, Breast, and Center for Cancer Therapeutic Innovation or CCTI), where the MatchMiner team worked directly with key departmental stakeholders to develop customized workflows. To facilitate access to MatchMiner among individual clinicians, we integrated the patient-centric and trial search modes into the Epic electronic health record. Other implementation strategies were piloted, such as weekly emails to clinicians alerting them to potential trial matches, but were less impactful. Overall, departmental collaborations have resulted in several ongoing MatchMiner initiatives. Thus far at DFCI, we have curated 354 PM trials into MatchMiner and facilitated 220 patient consents. For PM trials, 222 genes, 7 mutational signatures and nearly all cancer types were represented, demonstrating that there is a wide range of PM trial options available to patients. We also examined the distribution of trial phases and disease centers running each trial. The majority were Phase I and Phase II trials run out of the CCTI, consistent with the frequency with which novel drugs do not progress to later phase trials. Lastly, we have identified 220 trial consents that benefitted from MatchMiner. Retrospective analysis of a subset of these trial consents (n=166) revealed a significant 22% decrease in time to consent relative to other consents to the same trials, demonstrating the clinical impact of MatchMiner.

Citation Format: Harry Klein, Tali Mazor, Priti Kumari, Andrea Ovalle, Pavel Trukhanov, Jason Hansel, Joyce Yu, James Lindsay, Michael Hassett, Ethan Cerami. Design and adoption of MatchMiner at Dana-Farber Cancer Institute [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4091.

Abstract 1974: Immune gene expression signatures associated clinical benefit from nivolumab and ipilimumab for previously treated patients with stage IV squamous cell lung cancer: An immune biomarker analysis of phase III SWOG LungMAP S1400I trial

Background: In the Phase III randomized trial (SWOG Lung-MAP S1400I non match trial), adding ipilimumab (I) to nivolumab (N) did not improve survival of patients with advanced, pretreated, immune checkpoint inhibitor naive lung squamous cell carcinoma (SCC). The I+N combination demonstrated superiority in patients with a tumor mutation burden (TMB) ≥10 mt/MB and PD-L1 expression &lt;1% suggesting that a subset of patients may benefit from the addition of I. We leveraged specimens from S1400I to explore the immune signatures associated with outcome across both arms (I+N versus N) and investigate the potential superior benefit from I+N in SCC.

Methods: RNA extracted from baseline FFPE samples from 66/252 patients enrolled in the S1400I trial was received from the SWOG bank with 28 samples considered inadequate due to low input RNA. 38 samples were run on the ncounter platform using the PanCancer Immune Profiling panel using the manufacturer’s instructions with the addition of Human Reference RNA control. Data were processed and normalized using nSolver. All samples passed the post run QC with no batch effect. Using a log-rank test on dichotomized normalized data, we performed time to event analysis to identify genes that correlated with overall survival (OS) and PFS (Progression Free Survival) for all 38 samples and for each arm (23 N and 15 I+N). We ran a Cox model using significant genes identified independently and in association with TMB≥10 and PD-L1 ≥5 thresholds identified in the clinical studies. TIMER and nSolver advanced analysis were used to infer immune cells that correlated to clinical outcomes.

Results: We observed that BLNK, CD163, FCGR2A associated with increased OS (p&lt;0.01), IRF1 and BLNK associated with increased PFS (p&lt;0.01). FADD and MAPK11 associated with poor OS (p&lt;0.01). Cox model analysis confirmed that FADD and MAPK11 were associated with negative clinical outcomes (p&lt;0.05) while CD163 was associated with positive clinical outcome. Incorporating TMB and PD-L1 into the Cox model validated that MAP kinase activity resulted in a negative clinical outcome while CD163 correlated with positive clinical outcomes (p&lt;0.05). Focusing on immune signatures within the I+N arm, we observed higher CD45+ immune cell scores including exhausted CD8+ T cells and neutrophils in responders versus non-responders (p&lt;0.05).

Conclusion: Despite a small dataset, this analysis shows a potential advantage in PFS and OS with increased presence of immune cells including exhausted CD8+ T cells and genes associated with myeloid cells. Validation of these findings is warranted and may refine patient populations that would benefit from this combination strategy.

Acknowledgments: Scientific and financial support: U10CA180888, U10CA180819, U24CA224285, U24CA224316, PACT, PPP and FNIH

Citation Format: Dzifa Y. Duose, Jiexin Zhang, Mary Redman, Baili Zhang, Ethan Cerami, James Lindsay, Joyce Yu, Roshni Biswas, Stephen Van Nostrand, Radim Moravec, Rajyalakshmi Luthra, Gheath Al-Atrash, Karen Kelly, Roy Herbst, Ignacio Wistuba, Scott Gettinger, Lyudmila Bazhenova, J. Jack Lee, Jianjun Zhang, Cara Haymaker. Immune gene expression signatures associated clinical benefit from nivolumab and ipilimumab for previously treated patients with stage IV squamous cell lung cancer: An immune biomarker analysis of phase III SWOG LungMAP S1400I trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1974.

Abstract 506: Dissecting the genomic and tumor immune microenvironment factors associated with disease recurrence in resected stage I NSCLC

Background: Patients with early-stage non-small cell lung cancer (NSCLC) are at substantial risk for disease recurrence after surgical resection, and the discovery of biomarkers that predict disease recurrence has been challenging. We sought to identify genomic and immunologic factors associated with recurrence after surgery in stage I NSCLC.

Methods: We collected clinicopathologic data from patients with resected stage I NSCLC (AJCC 8th Edition) which underwent multiplexed immunofluorescence for CD8+, FOXP3+, PD-1+, and PD-L1. A subset of these samples also had next-generation sequencing performed to identify genomic alterations and tumor mutational burden (TMB). A bidirectional stepwise elimination was applied on variables with a univariable disease-free survival (DFS) p-value &lt;0.25. The final multivariable Cox model was validated with internal bootstrapping (B=300).

Results: A total of 252 cases were included. After a median follow-up of 25.6 months from the time of surgery, 47 cases (18.7%) experienced recurrence, with a 2-year DFS rate of 82.9%, and a 2-year overall survival (OS) rate of 97.9%. Shorter DFS was associated with higher TMB, increased PD-L1 expression, and greater numbers of intratumoral (IT) CD8+, PD-1+, and PD-1+CD8+ immune cells, as well as increased CD8+ and FOXP3+ T cells at the tumor stroma interface (TSI) in univariable analyses (p&lt;0.05). Multivariable analysis showed that shorter DFS was associated with increasing TMB and higher PD-L1 tumor cell expression. We observed a difference by immune cell localization and risk of recurrence: shorter DFS was associated with higher IT but lower TSI PD-1+ immune cells, and higher IT but lower TSI FOXP3+ T cells (Table). Internal bootstrap validation showed good model performance (C-index = 0.74).

Conclusion: Genomic analysis and immunophenotyping of stage I NSCLCs can identify cases at greatest risk of disease recurrence after surgical resection.

Table. Univariable and multivariable analysis Disease-free survival Univariable HR [95%CI] p-value Multivariable HR [95%CI] p-value Stage at diagnosis - 0.10 – – IA1 1.52 [0.58, 3.97] IA2 2.61 [0.95, 7.20] IA3 2.61 [1.03, 6.63] IB Histology - 0.42 Adenocarcinoma 1.38 [0.65, 2.97] Squamous Age* 1.02 [0.99, 1.06] 0.19 – – TMB* 1.09 [1.05, 1.12] &lt;0.001 1.09 [1.05, 1.13] &lt;0.001 Smoking* (pack-years) 1.01 [1.00, 1.02] 0.008 – – Smoking history - 0.012 – – Never 5.24 [1.27, 21.7] Former Current 4.92 [0.82, 29.5] Surgical treatment - 0.084 - 0.074 Lobectomy 1.80 [0.89, 3.62] 2.18 [0.93, 5.14] Sublobar Intratumoral** 1.09 [1.03, 1.16] 0.015 - – CD8+ 1.22 [1.10, 1.36] 0.002 1.80 [1.13, 2.87] 0.014 PD-1+ 1.51 [1.20, 1.90] 0.004 - – 0.004 PD-1+ CD8+ 1.22 [1.04, 1.44] 0.053 0.15 [0.04, 0.55] FOXP3+ Tumor-Stroma Interface** 1.06 [1.01, 1.11] 0.033 - - CD8+ 1.10 [1.01,1.20] 0.056 0.71 [0.56, 0.91] 0.007 PD-1+ 1.21 [0.99, 1.48] 0.100 - - PD-1+ CD8+ 1.28 [1.03, 1.59] 0.037 2.42 [1.49, 3.95] &lt;0.001 FOXP3+ PD-L1 expression* 1.02 [1.01, 1.03] &lt;0.001 1.03 [1.01, 1.04] &lt;0.001 Tumor Proportion Score (TPS) 1.02 [1.01, 1.04] - - Immune cells 0.011 *Per unit increase. ** Per 100 units increase. Intratumoral, is defined as the region of the slide consisting of tumor beyond the tumor-stroma interface. Tumor-Stroma Interface is defined as the region within 40 microns to either side of the defined border between tumor and stroma.

Citation Format: Joao Victor Alessi, Zihan Wei, Biagio Ricciuti, James Lindsay, Victor R. Vaz, Adriana Barrichello, Bijaya Sharma, Kristen D. Felt, Fangxin Hong, Lynette M. Sholl, Scott J. Rodig, Mark M. Awad. Dissecting the genomic and tumor immune microenvironment factors associated with disease recurrence in resected stage I NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 506.

Multiomics profiling and association with molecular and immune features in association with benefits from immunotherapy for patients with previously treated stage IV or recurrent squamous cell lung cancer from the phase III SWOG LungMAP S1400I trial

9046

Background: Immune checkpoint blockade (ICB) has become a standard pillar of treatment for lung cancer. However, only ̃20% of unselected patients can achieve durable clinical benefits. We performed immunogenomic profiling of tissue specimens from a randomized Phase III trial S1400I on metastatic lung squamous cell carcinoma (SCC) to evaluate if there were factors associated with better prognoses with ICB from single-agent versus combined targeting PD-1/CTLA-4 and evaluate if any differentiated between the treatments. Methods: We utilized FFPE tumor tissue submitted for Lung-MAP screening provided by the SWOG bank. SCC samples from 82 eligible patients treated with combined nivolumab+ipilimumab (N+I) or single agent nivolumab (N) were subjected to multiplex immunofluorescence (mIF, n = 82) and NanoString (ncounter PanCancer Immune Profiling Panel, n = 32). Cell density phenotypes (cells/mm2) were defined using image analysis of staining for cytokeratin, CD3, CD8, granzyme B, CD45RO, FOXP3, PD1, PD-L1, and CD68. Immunogenomic features were associated with response, PFS, and OS derived from data provided by the LungMap team to the CIDC portal. For statistical analyses, non-parametric tests were utilized to assess associations of cell phenotypes versus continuous or categorical variables, and log-rank test analysis was performed to identify cell phenotypes or genes correlated with survival. Results: In both arms higher densities of total CD3+CD45RO+ T cells ( P= 0.041), CD3+PD-1+ T cells ( P= 0.024) and CD3+CD8+PD-1 T cells in stroma ( P= 0.042) and CD3+CD8+GZMB+ T cells in the tumor compartment ( P= 0.011) were positively associated with PFS. In the N+I arm but not in the N arm, higher densities of CD3+CD8+GZMB+ T cells in the tumor compartment were associated with better PFS ( P= 0.015) and higher densities of stroma CD3+CD8-FOXP3+ T cells with worse OS. Spatial analysis showed that the presence of CD8+GZMB+ T cells close to malignant cells (median, ≤19.27 µm) was associated with better PFS ( P= 0.037) in N+I arm and cluster analysis showed low clustering of cells in TMB-high vs. TMB-low tumors (P < 0.01). Gene expression profiling demonstrated that myeloid infiltration, immune recruitment, and inflammation genes were associated with a positive clinical outcome ( P< 0.05). In both arms, BLNK, CD163, FCGR2A were associated with better OS ( P< 0.01), IRF1 and BLNK were associated with increased PFS ( P< 0.01). In the N+I arm but not in the N arm, we observed significantly higher CD45 immune cell scores, including CD8 T cells and neutrophils, in responders versus non-responders. Conclusions: Our findings suggest a potential advantage in PFS and OS with an increased presence of cytotoxic immune cells and genes associated with the recruitment and proliferation of these cell types before therapy.

Three-year outcomes and correlative analyses in patients with non–small cell lung cancer (NSCLC) and a very high PD-L1 tumor proportion score (TPS) ≥ 90% treated with first-line pembrolizumab

9043

Background: Although 1st-line PD-1 monotherapy has improved survival in advanced NSCLC with a PD-L1 TPS ≥50%, responses occur in ̃45% of patients (pts). We previously showed that among pts treated with 1st-line pembrolizumab, clinical outcomes were significantly improved in those with a PD-L1 TPS of ≥90% compared to a TPS of 50-89%. Here, we report the 3-year survival analysis to 1st-line pembrolizumab in pts with a PD-L1 TPS ≥90% vs 50-89%, and characterize genomic and immunophenotypic differences between these PD-L1 expression groups. Methods: Pts with stage IV EGFR/ALK wild-type NSCLC and PD-L1 TPS ≥50% who received 1st-line pembrolizumab at the Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering Cancer Center (MSKCC), with a minimum follow-up of 3 years were included. Comprehensive tumor genomic profiling and multiplexed immunofluorescence (mIF) were performed to examine genomic and immunophenotypic correlates of very high PD-L1 expression on separate cohorts of NSCLC at the DFCI. Results: Among 396 pts, median age was 69, 53.3% were women, 90.1% had a history of tobacco use, 83.6% had a ECOG performance status of 0-1, and 28.8% had a KRAS mutation. At a median follow-up of 42.6 months, median progression-free (mPFS) and overall survival (mOS) in the entire cohort were 5.1 months, and 19.0 months, respectively. When compared to pts with a PD-L1 TPS of 50-89% (N = 252), those with PD-L1 TPS ≥90% (N = 144) had a significantly longer mPFS (6.0 vs 4.5 months, HR 0.67, p < 0.001), and longer mOS (30.2 vs 16.9 months, HR 0.66, p < 0.01). Kaplan-Meier estimates of the 3-year PFS and OS were 24.9% and 47.0% in the PD-L1 TPS ≥90% groups, and 9.4% and 27.7% in the PD-L1 TPS 50-89% group, respectively. A PD-L1 TPS ≥90% was confirmed to be an independent predictor of improved PFS (HR 0.68, p < 0.01) and OS (HR 0.67, p < 0.01) in multivariable analysis. Tumor genomic profiling from a separate cohort of 500 NSCLC samples revealed that mutations in STK11, KEAP1, FBXW7, and CTNNB1 were significantly more frequent in tumors with a PD-L1 TPS of 50-89% compared to those with a PD-L1 TPS ≥90% (q < 0.05). mIF on 91 NSCLCs identified significantly higher CD8+PD1+ T cells and PD-L1+ immune cells in tumors with PD-L1 TPS ≥90% vs 50-89% (p < 0.05). Conclusions: Pembrolizumab monotherapy continues to demonstrate a meaningful long-term survival benefit in pts with advanced NSCLC and a PD-L1 TPS ≥90%. NSCLCs with very high PD-L1 TPS may have a more favorable genomic and immunophenotypic profile. These findings have implications for treatment selection and clinical trial interpretation and design.

Use of Whole Genome Sequencing by the Federal Interagency Collaboration for Genomics for Food and Feed Safety in the United States

ABSTRACT

This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

HIGHLIGHTS

A145 EFFICACY AND SAFETY OF UPADACITINIB MAINTENANCE THERAPY IN PATIENTS WITH MODERATELY TO SEVERELY ACTIVE ULCERATIVE COLITIS: RESULTS FROM A RANDOMIZED PHASE 3 STUDY

Background

Upadacitinib (UPA), an oral selective and reversible JAK inhibitor, demonstrated significantly greater efficacy compared with placebo (PBO) for induction of remission in patients with moderately to severely active ulcerative colitis (UC) in two phase 3 induction trials.

Aims

Evaluate safety and efficacy of 52 weeks of UPA 15 mg QD (UPA15) and 30mg QD (UPA30) compared to placebo in patients achieving clinical response following UPA 45 mg treatment in the induction trials.

Methods

The primary analysis (n=451) evaluated efficacy and safety of UPA15 and UPA30 compared to PBO as maintenance therapy. The primary endpoint was clinical remission via adapted Mayo score at wk 52. Ranked secondary endpoints included endoscopic improvement, maintenance of clinical remission, corticosteroid-free clinical remission, maintenance of endoscopic improvement, endoscopic remission, maintenance of clinical response and Histologic-endoscopic mucosal improvement (HEMI).

Results

Baseline characteristics were similar between all treatment groups. Both UPA15 and UPA30 met the primary endpoint, and all secondary endpoints. Significantly greater percentages of patients receiving UPA15 and UPA30 vs. PBO achieved clinical remission (42.3% and 51.7%, vs. 12.1%), endoscopic improvement (48.7% and 61.6%, vs. 14.5%), maintenance of clinical remission (59.2% and 69.7%, vs. 22.2%), corticosteroid-free clinical remission (57.1% and 68.0%, vs. 22.2%), maintenance of endoscopic improvement (61.6% and 69.5%, vs. 18.9%), endoscopic remission, (24.2% and 25.9%, vs. 5.6%) and HEMI (34.8% and 49.3%, vs. 11.8%) (p<0.001 for all endpoints). UPA15 and UPA30 were both well-tolerated and no new safety signals were observed. Rates for serious adverse events (AEs) and AEs leading to treatment discontinuation were similar between UPA15 and UPA30 groups and lower compared to the PBO group. Most common AEs were nasopharyngitis and creatine phosphokinase elevation among UPA groups and UC exacerbation within the PBO group (30.2%). Herpes zoster was only reported in UPA groups (3.9%-4.1%). Similar rates of malignancy excluding NMSC were seen within all groups (0.7%-1.3%). MACE were only reported among patients receiving PBO (0.7%), while VTE were only found with UPA30 (1.3%).

Conclusions

In patients responding to UPA induction therapy, both UPA15 and UPA30 were safe and effective as maintenance treatment at 52 wk for all primary and secondary endpoints. Patients receiving UPA30 responded approximately 10% better for most endpoints compared to those receiving UPA15. Both doses were well-tolerated, with no new safety signals observed.

Funding Agencies

AbbVie

Abstract P160: MatchMiner: An open-source platform for cancer precision medicine

With the advent of next generation sequencing in cancer care, patients’ tumors can be genomically profiled and specific genetic alterations can be targeted with precision medicine drugs. However, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to precision medicine trials. To facilitate interpretation of complex tumor sequencing data and clinical trial genomic eligibility criteria, we developed MatchMiner, an open-source platform to computationally match cancer patients to precision medicine clinical trials. MatchMiner has several modes of clinical use: (1) patient-centric, where clinicians look up trial matches for their patient, (2) trial-centric, where clinical trial investigators identify patients for their clinical trials, and (3) trial search, where clinicians identify available trials based on any criteria, including external genomic reports. To support users in all three modes, MatchMiner also displays full genomic reports for patients and detailed trial information in user-friendly formats. MatchMiner trial matching is performed via the MatchEngine, an algorithm that computes matches based on patient genomic and clinical data and trial eligibility criteria. The MatchEngine accepts many different data inputs for patient-trial matching, and is easily customized to work with data available at any institution. At Dana-Farber Cancer Institute (DFCI), MatchMiner supports the following data: 1) patient-specific genomic sequencing data, including mutations, copy number alterations, structural variants, tumor mutational burden and mutational signatures including mismatch repair deficiency or microsatellite instability, 2) patient-specific clinical data, including primary cancer type, gender, age, and vital status, and 3) trial eligibility criteria including genomic targets, cancer type, and age. Unique to MatchMiner, each trial’s eligibility criteria is encoded in clinical trial markup language (CTML), a structured format that encodes detailed information about a trial and utilizes boolean logic to encode inclusion and exclusion criteria. Although MatchMiner has been operational at DFCI since early 2017, its impact on patient care has not yet been extensively studied. Thus far, MatchMiner has facilitated 181 precision medicine trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner’s impact on trial consent, we retrospectively measured time from genomic sequencing report date to trial consent date for a subset of the 181 MMC (166 MMC). We compared time to trial consent date for the 166 MMC to a group of 353 consents for the same trials not facilitated by MatchMiner (non-MatchMiner consents, non-MMC). MMC consented to trials 22% faster (P=0.004, median=195 days, IQR=85-34) than non-MMC (median=250 days; IQR=99-491). Thus, clinical use of MatchMiner decreased time to enroll in a precision medicine study, and suggests that use of precision medicine trial matching tools such as MatchMiner are important for the future of patient care.

Citation Format: Harry Klein, Tali Mazor, Priti Kumari, James Lindsay, Andrea Ovalle, Pavel Trukhanov, Joyce Yu, Michael Hassett, Ethan Cerami. MatchMiner: An open-source platform for cancer precision medicine [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P160.

Low peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) is associated with increased tumor T-cell infiltration and favorable outcomes to first-line pembrolizumab in non-small cell lung cancer

BACKGROUND

An elevated peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) is a negative prognostic marker for patients with non-small cell lung cancer (NSCLC) receiving chemotherapy and immune checkpoint inhibitors. Whether dNLR is also associated with clinical outcomes to first-line pembrolizumab among patients with NSCLC and a programmed cell death ligand 1 (PD-L1) Tumor Proportion Score (TPS) of ≥50% is uncertain. How dNLR relates to the tumor immune microenvironment is also unclear.

METHODS

In two participating academic centers, we retrospectively analyzed the dNLR (defined as the absolute neutrophil count/white cell count - absolute neutrophil count) prior to initiation of first-line pembrolizumab in patients with metastatic NSCLC and a PD-L1 TPS ≥50% and lacking genomic alterations in EGFR and ALK. An unbiased recursive partitioning algorithm was used to investigate an optimal dNLR cut-off with respect to objective response rate (ORR). Multiplexed immunofluorescence for CD8+, FOXP3+, PD-1+, and PD-L1 was performed on a separate cohort of NSCLCs to determine the immunophenotype associated with dNLR.

RESULTS

A total of 221 patients treated with first-line pembrolizumab were included in this study. The optimal dNLR cut-off to differentiate treatment responders from non-responders was 2.6. Compared with patients with a dNLR ≥2.6 (n=97), patients with dNLR <2.6 (n=124) had a significantly higher ORR (52.4% vs 24.7%, p<0.001), a significantly longer median progression-free survival (mPFS 10.4 vs 3.4 months, HR 0.48, 95% CI 0.35 to 0.66, p<0.001), and a significantly longer median overall survival (mOS 36.6 vs 9.8 months, HR 0.34, 95% CI 0.23 to 0.49, p<0.001). After adjusting for age, sex, tobacco use, performance status, histology, serum albumin level, oncogenic driver status, and PD-L1 distribution (50%-89% vs ≥90%), a dNLR <2.6 was confirmed to be an independent predictor of longer mPFS (HR 0.47, 95% CI 0.33 to 0.67, p<0.001) and mOS (HR 0.32, 95% CI 0.21 to 0.49, p<0.001). Among advanced NSCLC samples with a PD-L1 TPS of ≥50%, those with a dNLR <2.6 had significantly higher numbers of tumor-associated CD8+, FOXP3+, PD-1 +immune cells, and PD-1 +CD8+T cells than those with a dNLR ≥2.6.

CONCLUSIONS

Among patients with NSCLC and a PD-L1 TPS ≥50%, a low dNLR has a distinct immune tumor microenvironment and more favorable outcomes to first-line pembrolizumab.

67 Cancer aneuploidy is associated with a distinct tumor immune microenvironment and impacts outcomes to immune checkpoint inhibition in nonsquamous non-small cell lung cancer

Background

Cancer aneuploidy, an unbalanced number of chromosomes, is associated with somatic mutation rate, expression of proliferative genes, and altered immune signaling. Whether aneuploidy correlates with a distinct tumor immunophenotype or impacts clinical outcomes to immune checkpoint inhibitors (ICIs) in NSCLC is unclear.

Methods

Among nonsquamous NSCLCs which underwent targeted next-generation sequencing, we retrospectively quantified aneuploidy using the fraction of chromosomal arm alterations (FAA), defined as the number of aneuploid chromosome arms divided by the number of chromosome arms assessed. An unbiased recursive partitioning algorithm was used to investigate an FAA level which best discriminated responders from non-responders to ICIs. Multiplexed immunofluorescence to quantify CD8, FOXP3, and PD-1-positive cell counts, as well as PD-L1 expression was performed on a separate cohort of nonsquamous NSCLCs to determine differences in tumor immune cells subsets according to FAA levels.

Results

Among 1426 nonsquamous NSCLCs identified, FAA increased along with the increase of pathologic stage, and was highest among tumors harboring EGFR mutations and RET fusions, and lowest among those with KRAS, BRAF, and MET mutations. FAA inversely correlated with PD-L1 expression levels, and positively correlated with tumor mutational burden (TMB) (figure 1A-D). Among 281 NSCLCs treated with ICIs, the median FAA was significantly lower among patients with a partial response to ICI compared to those with stable or progressive disease (0.11 vs 0.21, P=0.006). A fractional aneuploidy level of 0.06 (representing the lowest quartile of FAA) was identified as an optimal cutpoint to discriminate responders from non-responders to ICI. Compared to pts with an FAA >0.06 (N=212), pts with FAA ≤0.06 (N=69) had a significantly higher ORR (42.0% vs 19.3%, P<0.001), longer median progression-free survival (mPFS 6.8 vs 3.2 months, HR: 0.64, P=0.004), and longer median overall survival (mOS 24.8 vs 13.8 months, HR: 0.65, P=0.012) with ICIs (figure 2). After adjusting for performance status, PD-L1 expression, TMB, and line of treatment, FAA retained a significant association with improved PFS (HR: 0.66, P=0.018) and OS (HR: 0.66, P=0.041) to immunotherapy. FAA had no impact on clinical outcomes among pts who received first-line platinum doublet chemotherapy without ICI (figure 3). Among 239 nonsquamous NSCLCs profiled by multiplex immunofluorescence, cancers with a low FAA (≤25th percentile) were significantly enriched in CD8+ T cells and had a higher CD8+ to FOXP3+ ratio compared to those with high FAA (>25th percentile) (figure 4).

Abstract 67 Figure 1

(A) Median fraction of chromosomal alterations (FAA) are shown for stages I, II, III, and IV NSCLCs. (B) Tumors with negative (<1%), low (1–49%), and high PD-L1 tumor proportion score (TPS) (≥50%) expression. (C) Pearson’s correlation coefficient between FAA and tumor mutational burden (TMB). (D) Median FAA distribution across a set of 8 targetable driver mutations (ALK, BRAF, EGFR, HER2, KRAS, MET, RET and ROS1) and none identified alteration.

Abstract 67 Figure 2

(A) Objective response rate, (B) progression-free survival, and (C) overall survival, in patients with a fraction of chromosomal arm alterations (FAA) ≤0.06 versus >0.06 in the immunotherapy-cohort.

Abstract 67 Figure 3

(A) Objective response rate and (B) progression-free survival (PFS) in patients with a fraction of chromosomal arm alterations (FAA) ≤0.06 versus >0.06 in the chemotherapy-cohort.

Abstract 67 Figure 4

(A) CD8+, (B) PD-1+, (C) PD-1+ CD8+ (D), FOXP3+ cells/mm2, and (E) PD-L1 distribution in nonsquamous NSCLCs with an fraction of arm-level altered (FAA) low (≤25th percentile) versus high (>25th percentile). (F) CD8+ to FOXP3+ ratio in tumors with FAA low versus FAA high.

Conclusions

Nonsquamous NSCLCs with low aneuploidy have a distinct immune microenvironment and more favorable outcomes to ICIs.

Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial-Ready Patients With Cancer

PURPOSE

To inform precision oncology, methods are needed to use electronic health records (EHRs) to identify patients with cancer who are experiencing clinical inflection points, consistent with worsening prognosis or a high propensity to change treatment, at specific time points. Such patients might benefit from real-time screening for clinical trials.

METHODS

Using serial unstructured imaging reports for patients with solid tumors or lymphoma participating in a single-institution precision medicine study, we trained a deep neural network natural language processing (NLP) model to dynamically predict patients' prognoses and propensity to start new palliative-intent systemic therapy within 30 days. Model performance was evaluated using Harrell's c-index (for prognosis) and the area under the receiver operating characteristic curve (AUC; for new treatment and new clinical trial enrollment). Associations between model outputs and manual annotations of cancer progression were also evaluated using the AUC.

RESULTS

A deep NLP model was trained and evaluated using 302,688 imaging reports for 16,780 patients. In a held-out test set of 34,770 reports for 1,952 additional patients, the model predicted survival with a c-index of 0.76 and initiation of new treatment with an AUC of 0.77. Model-generated prognostic scores were associated with annotation of cancer progression on the basis of manual EHR review (n = 1,488 reports for 110 patients with lung or colorectal cancer) with an AUC of 0.78, and predictions of new treatment were associated with annotation of cancer progression on the basis of manual EHR review with an AUC of 0.84.

CONCLUSION

Training a deep NLP model to identify clinical inflection points among patients with cancer is feasible. This approach could identify patients who may benefit from real-time targeted clinical trial screening interventions at health system scale.

SMARCA4 and Other SWItch/Sucrose NonFermentable Family Genomic Alterations in NSCLC: Clinicopathologic Characteristics and Outcomes to Immune Checkpoint Inhibition

INTRODUCTION

The SWItch/Sucrose Nonfermentable (SWI/SNF) chromatin remodeling complex acts as a regulatory component of transcription, and inactivating mutations (muts) within the complex are implicated in genomic instability, higher tumor mutational burden, and an aggressive cancer phenotype. Whether SMARCA4 and other SWI/SNF alterations are independent prognostic factors or associated with clinical outcomes to immune checkpoint inhibitors (ICIs) in NSCLC remains unclear.

METHODS

We collected clinicopathologic and genomic data from patients with NSCLC who underwent targeted next-generation sequencing at the Dana-Farber Cancer Institute. Tumors were characterized on the basis of the presence or absence of muts across a set of six SWI/SNF genes (ARID1A, ARID1B, ARID2, PBRM1, SMARCA4, and SMARCB1).

RESULTS

Of 2689 patients with NSCLC, 20.6% (N = 555) had SWI/SNF genomic alterations. Compared with SWI/SNF wild-type (wt) NSCLC, patients with SWI/SNF-mutant NSCLCs had a lower prevalence of concurrent targetable driver muts (33.2% versus 22.2%; p < 0.001), a higher tumor mutational burden (median 8.5 versus 12.2 muts/megabase; p < 0.001), and a shorter median overall survival (mOS) from the time of advanced disease diagnosis (25.0 versus 19.3 mo, p = 0.01); the detrimental effect in OS seemed to be largely driven by SMARCA4 muts (mOS: 25.0 for SMARCA4 wt versus 15.6 mo for SMARCA4 mutant; p < 0.001). Among 532 patients who received ICIs, 25.5% (N = 136) harbored SWI/SNF muts. From the start of immunotherapy, there was no difference in objective response rate (ORR = 19.9% versus 25.0%, p = 0.2), median progression-free survival (mPFS = 3.0 versus 3.0 mo, hazard ratio [HR] = 0.96 [95% confidence interval [CI] = 0.77-1.18], p = 0.7), or mOS (13.1 versus 9.5 mo, HR = 0.81 [95% CI: 0.64-1.02], p = 0.07) in SWI/SNF-wt versus SWI/SNF-mutant NSCLC, respectively. Nevertheless, among KRAS-mutant NSCLCs treated with ICIs (N = 176), a concurrent SWI/SNF mut (N = 39) conferred a numerically lower ORR (21.9% versus 12.8%, p = 0.2), a significantly shorter mPFS (4.1 versus 1.8 mo, HR = 0.57 [95% CI: 0.38-0.84], p = 0.005), and a significantly shorter mOS (15.5 versus 8.2 mo, HR = 0.56 [95% CI: 0.36-0.86], p = 0.008). The deleterious effect on immunotherapy outcomes in KRAS-mutant NSCLC was most pronounced in the SMARCA4-mutant subset (N = 17), with a lower ORR (22% versus 0%, p = 0.03), a significantly shorter mPFS (4.1 versus 1.4 mo, HR = 0.25 [95% CI: 0.14-0.42], p < 0.001), and a significantly shorter mOS (15.1 versus 3.0 mo, HR = 0.29 [95% CI: 0.17-0.50], p < 0.001) compared with SMARCA4-wt KRAS-mutant NSCLCs.

CONCLUSIONS

Although there were no associations between SWI/SNF mut status and immunotherapy efficacy in the overall NSCLC cohort, the presence of a SMARCA4 alteration may confer a worse outcome to immunotherapy among KRAS-mutant NSCLCs.

Abstract 1198: MatchMiner: An open-source computational platform that accelerates patient enrollment on to precision medicine trials

With the advent of next generation sequencing in cancer care, patients' tumors can be genomically profiled and specific genetic alterations can be targeted with precision medicine drugs. However, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to precision medicine trials. To facilitate interpretation of complex tumor sequencing data and clinical trial genomic eligibility criteria, we developed MatchMiner, an open-source platform to computationally match cancer patients to precision medicine clinical trials. MatchMiner supports two distinct workflows: (1) patient-centric mode, in which an oncologist can find clinical trial matches for a specific patient, and (2) trial-centric mode, in which a clinical trial investigator can identify and recruit patients for a specific trial. In MatchMiner at DFCI, there are currently 330+ precision medicine trials and genomic and genomic and clinical data from 39,000+ patients. Although MatchMiner has been operational at Dana-Farber Cancer Institute since early 2017, its impact on patient care has not yet been extensively studied.

In this study, we analyzed temporal trends of 170 MatchMiner-driven trial enrollments. We compared these 170 MatchMiner-driven trial enrollments to non-MatchMiner-driven trial enrollments to determine how MatchMiner has impacted patient enrollments. To compare MatchMiner-driven trial enrollments to non-MatchMiner-driven enrollments, we limited the non-MatchMiner group by choosing patients who enrolled on the same trials. We also ensured that all patients in both enrollment groups had a genomic report present in MatchMiner before their consent date. We then analyzed temporal trends between genomic report dates, patient consent and on-study dates, and patient views in MatchMiner. MatchMiner-driven enrollments had a significant decrease in time from genomic report date to consent date compared to non-MatchMiner-driven enrollments. Thus, clinical use of MatchMiner decreased time to enroll in a precision medicine study, and suggests that use of precision medicine trial matching tools such as MatchMiner are important for the future of patient care.

The MatchMiner open-source software package is available through GitHub (https://github.com/dfci/matchminer). We are committed to supporting MatchMiner as an open-source software; to our knowledge, at least five cancer centers are implementing MatchMiner.

Citation Format: Harry Klein, Tali Mazor, Priti Kumari, James Lindsay, Andrea Ovalle, Ethan Siegel, Pavel Trukhanov, Joyce Yu, Michael Hassett, Ethan Cerami. MatchMiner: An open-source computational platform that accelerates patient enrollment on to precision medicine trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1198.

Abstract 26: Association of aneuploidy score with clinical outcomes to immunotherapy in NSCLC

Introduction: Cancer aneuploidy, an unbalanced number of chromosomes, is associated with somatic mutation rate, expression of proliferative genes, and altered immune signaling. Whether aneuploidy impacts clinical outcomes to immune checkpoint inhibitors (ICIs) in NSCLC is unknown.

Methods: In NSCLCs which underwent targeted next-generation sequencing (NGS), we retrospectively analyzed the aneuploidy score (AS), defined as the sum of the number of altered chromosome arms, among patients treated with immune checkpoint inhibitors. An unbiased recursive partitioning (URP) algorithm was used to investigate an optimal AS cut-off with respect to objective response rate (ORR). Multiplexed immunofluorescence (mIF) to quantify CD8+, FOXP3+, PD-1+ immune cells, and PD-L1 was performed to determine differences in tumor immune cells subsets according to AS cut-off.

Results: Among 279 patients with NSCLC treated with ICIs, the median AS was 6 (range 0 to 23). The AS was significantly lower among patients with a partial response to ICI compared to those with stable or progressive disease (4 vs 7, P=0.004). An unbiased recursive partitioning analysis identified an AS of 2 as the strongest discriminator of objective response to ICI. Compared to patients with an AS &gt;2 (N= 207, 74.2%), patients with AS ≤2 (N=72, 25.8%) had a significantly higher overall response rate (ORR 43.0% vs 19.8%, P&lt;0.001), a significantly longer median progression free survival (mPFS 6.2 months vs 2.9 months, HR: 0.70 [95% CI: 0.52-0.94], P=0.02), and a significantly longer median overall survival (mOS 19.8 months versus 13.8 months, HR: 0.66 [95% CI: 0.47-0.94], P=0.02) to treatment with ICIs. After adjusting for other variables such as performance status, presence of oncogenic driver mutation, PD-L1 expression, tumor mutational burden, and line of treatment, AS was significantly associated with improved mPFS (HR: 0.72 [95% CI: 0.52-0.99], P=0.04) and mOS (HR: 0.64 [95% CI: 0.44-0.94], P=0.02). Among 179 NSCLCs profiled by multiplex immunofluorescence, compared to cancers with an AS &gt;2, those with low aneuploidy (AS ≤2) had significantly higher numbers of CD8+, FOXP3+, PD-1+ immune cells, and PD-1+ CD8+ T cells, both intratumorally and when looking at the total numbers of cells within the tumor and the tumor-stroma interface. There was no significant difference in PD-L1 expression levels or tumor mutational burden on tumor cells or on immune cells according to aneuploidy score.

Conclusion: NSCLCs with low aneuploidy have a distinct immune microenvironment and more favorable outcomes to ICIs.

Citation Format: João Victor Alessi, Biagio Ricciuti, Yvonne Y. Li, Hersh Gupta, Giuseppe Lamberti, Gonzalo Recondo, Mizuki Nishino, Lynette M. Sholl, Andrew D. Cherniak, James Lindsay, Bijaya Sharma, Kathleen Pfaff, Kristen Felt, Scott Rodig, Mark M. Awad. Association of aneuploidy score with clinical outcomes to immunotherapy in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 26.

Abstract 490: A very high tumor mutational burden (TMB) is associated with improved efficacy of PD-(L)1 inhibition across different PD-L1 expression subgroups and a distinct immunophenotype in NSCLC

Background: Although high TMB correlates with improved outcomes to immune checkpoint inhibitors (ICI) in patients (pts) with non-small cell lung cancer (NSCLC), an optimal TMB cut-off to discriminate cancers most likely to respond to ICI has not been identified. Whether TMB impacts outcomes to ICI in different PD-L1 levels subgroups is also unclear.

Methods: Unbiased recursive partitioning (URP) was used to identify an optimal TMB cut-off for objective response rate (ORR) in two independent cohorts (DFCI and MSKCC) of pts with NSCLC treated with ICI. TCGA was interrogated to find differences in tumor immune cell subsets according to the TMB cut-off identified. Multiplexed immunofluorescence (IP) was also performed on NSCLC samples.

Results: In the DFCI (N=686) and MSKCC (N=672) cohorts, URP found an optimal cut-off of TMB for ORR at 19 mutations/megabase (mut/Mb), corresponding to the 90th percentile in each cohort. Median progression-free (PFS) and overall survival (OS) were significantly longer in NSCLCs with TMB ≥19 mut/Mb vs &lt;19 mut/Mb, in both cohorts (Table). After harmonizing TMB between DFCI OncoPanel and MSK-IMPACT NGS platforms, URP confirmed an optimal TMB cut-off for ORR at the 90th percentile in the combined cohort, which also associated with longer PFS/OS (Table). A TMB ≥90th percentile correlated with longer PFS/OS among NSCLCs with PD-L1 levels ≥50% and 1-49%, and longer PFS among those with PD-L1 &lt;1% (Table). Cell subset transcriptome analysis from the TCGA showed higher proportions of CD8+ T cells (P=0.02) and M1 macrophages (P&lt;0.01), among NSCLCs with a TMB ≥ vs &lt;90th percentile. IP confirmed increased CD8+ and CD8+/PD1+ T-cell infiltration (P&lt;0.01) in NSCLC with very high TMB.

Conclusion: A very high TMB is associated with better outcomes to ICI and a distinct immunophenotype in NSCLC. Rational integration of TMB and PD-L1 expression may identify NSCLCs most likely to respond to ICI.

CohortPD-L1 expressionPFS TMB ≥ vs &lt;90th percentile HR [95%CI],POS TMB ≥ vs &lt;90th percentile HR [95%CI],PDFCI N=6860-1000.48 [0.36-0.65],P&lt;0.010.57 [0.41-0.78],P&lt;0.01MSKCC N=6720-1000.38 [0.28-0.52],P&lt;0.010.46 [0.33-0.65],P&lt;0.01DFCI+MSKCC0-1000.44 [0.35-0.54],P&lt;0.010.50 [0.39-0.64],P&lt;0.01DFCI+MSKCC≥50%0.52 [0.34-0.81], P&lt;0.010.54 [0.32-0.94],P=0.031-49%0.33 [0.19-0.57],P&lt;0.010.36 [0.19-0.69], P&lt;0.01&lt;1%0.40 [0.25-0.65], P&lt;0.010.72 [0.34-1.18],P=0.19

Citation Format: Biagio Ricciuti, Kathryn C. Arbour, Navin R. Mahadevan, Joao V. Alessi, James Lindsay, Renato Umeton, Rileen Sinha, Amir Hoojghan, Natalie Vokes, Gonzalo Recondo, Giuseppe Lamberti, Andrew Polio1, Hira Rizvi, Giulia Leonardi, Andrew J. Plodkowski, Kristen Felt, Bijaya Sharma, Michael Y. Tolstorukov, Pasi A. Janne, Eliezer M. Van Allen, Lynette M. Sholl, Scott J. Rodig, Matthew D. Hellmann, Mark M. Awad. A very high tumor mutational burden (TMB) is associated with improved efficacy of PD-(L)1 inhibition across different PD-L1 expression subgroups and a distinct immunophenotype in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 490.

Clinicopathologic and genomic correlates of tumor-infiltrating immune cells and immunotherapy efficacy in NSCLC

9121

Background: Tumor-infiltrating immune cells and PD-L1 expression are associated with improved clinical outcomes in patients (pts) with NSCLC treated with immune checkpoint inhibitors (ICIs). However, as tumor-infiltrating immune cells are not a well-established biomarker for NSCLC, further data are needed to integrate and identify clinicopathological and genomic factors that influence the tumor microenvironment. Methods: We collected clinicopathologic and genomic data from pts with NSCLC who underwent multiplexed immunofluorescence. Uniform Manifold Approximation and Projection (UMAP) was used to identify distinct immunophenotypic clusters according to the number of intratumoral PD-1+ immune cells (ICs), CD8+, and Foxp3+ T cells, as well as PD-L1 on tumor and immune cells. An unbiased recursive partitioning (URP) algorithm was used to investigate an optimal cluster with respect to objective response rate (ORR) in the subset of pts treated with ICIs. Results: Among 304 pts, UMAP identified 5 clusters: PD-L1-high with high vs low CD8+ and PD-1+ ICs (clusters A & B, respectively); PD-L1-low with high vs low CD8+ and PD-1+ ICs (clusters C & D respectively); PD-L1-low and moderate levels of CD8+ and PD-1+ ICs (cluster E). Clinicopathological characteristics of the clusters shown in Table. URP analysis identified immune rich clusters A and C as optimal responders to ICIs. From the start of ICIs, we observed a significantly higher ORR (53.3% vs 4.3%; P<0.001), a significantly longer median progression-free survival (mPFS 25.6 vs 3.7 months; HR: 0.12 [95% CI: 0.05-0.32]; P<0.001), and longer median overall survival (mOS 45.1 vs 22.3 months; HR: 0.25 [95% CI: 0.1-0.68]; P=0.006) in clusters A + C (N=15) vs other clusters (N=23). After adjusting for other variables such as performance status, histology, presence of oncogenic driver mutation, and line of treatment, clusters A + C were significantly associated with improved mPFS (HR: 0.08 [95% CI: 0.03-0.24], P<0.001) and mOS (HR: 0.11 [95% CI: 0.03-0.40], P<0.001). Conclusions: Incorporation of multiplex immunofluorescence may improve prediction of response and resistance to immunotherapy in NSCLC.[Table: see text]

Association of a very high tumor mutational load with increased CD8+ and PD-1+ T-cell infiltration and improved clinical outcomes to PD-(L)1 blockade across different PD-L1 expression levels in non-small cell lung cancer

9018

Background: Although high TMB correlates with improved outcomes to immune checkpoint inhibitors (ICI) in patients (pts) with non-small cell lung cancer (NSCLC), an optimal TMB cutoff to discriminate cancers most likely to respond to ICI has not been identified. Whether TMB impacts outcomes to ICI in different PD-L1 levels subgroups is also unclear. Methods: Unbiased recursive partitioning (URP) was used to identify an optimal TMB cutoff for objective response rate (ORR) in two independent cohorts of pts with NSCLC treated with ICI at DFCI and MSKCC. TCGA was interrogated to find differences in tumor immune cell subsets according to the TMB cutoff identified. Multiplexed immunofluorescence (IF) for CD8, PD-1, PD-L1, Foxp3, and CK7 was also performed on NSCLC samples at the DFCI. Results: In the DFCI (N=686) and MSKCC (N=672) cohorts, URP found an optimal TMB cutoff for ORR at 19 mutations/megabase (mut/Mb), corresponding to the ̃90th percentile in each cohort. Median progression-free (PFS) and overall survival (OS) were significantly longer in NSCLCs with TMB ≥19 mut/Mb vs <19 mut/Mb, in both cohorts (Table). After harmonizing TMB between DFCI OncoPanel and MSK-IMPACT NGS platforms, URP confirmed an optimal TMB cutoff for ORR at the 90th percentile in the combined cohort, which also associated with longer PFS/OS to ICI (Table). A TMB ≥90th percentile correlated with longer PFS/OS to ICI among NSCLCs with PD-L1 levels ≥50% and 1-49%, and longer PFS among those with PD-L1 <1% (Table). Cell subset transcriptome analysis from the TCGA showed higher proportions of CD8+ T cells (P=0.02) and M1 macrophages (P<0.01) among NSCLCs with a TMB ≥ vs <90th percentile. IF confirmed increased CD8+, CD8+ PD1+ T-cell infiltration (P<0.01), and increased CD8+/Foxp3+ ratio in NSCLC with very high TMB Conclusions: A very high TMB is associated with better outcomes to ICI and a distinct immunophenotype in NSCLC. Rational integration of TMB and PD-L1 expression may identify NSCLCs most likely to respond to ICI.[Table: see text]

Clinicopathologic, genomic, and tumor microenvironment correlates of aneuploidy and immunotherapy outcomes in NSCLC

9119

Background: Cancer aneuploidy, an unbalanced number of chromosomes, is associated with somatic mutation rate, expression of proliferative genes, and altered immune signaling. Whether aneuploidy correlates to a distinct immunophenotype or impacts clinical outcomes to immune checkpoint inhibitors (ICIs) in NSCLC is unclear. Methods: In NSCLCs which underwent targeted next-generation sequencing, we retrospectively analyzed the aneuploidy score (AS), defined as the sum of the number of altered chromosome arms. An unbiased recursive partitioning (URP) algorithm was used to investigate an AS cutoff to discriminate responders from non-responders to ICIs. Multiplexed immunofluorescence to quantify CD8+, Foxp3+, PD-1+, and PD-L1 expression was performed to determine differences in tumor immune cells subsets according to AS cutoff. Results: Among 436 NSCLCs identified, stage I tumors (median AS 1) had significantly lower median AS (mAS) than stage IV cancers (mAS 7, P < 0.001), stage III (mAS 4, P = 0.03), and numerically lower compared to stage II cancers (mAS 3, P = 0.18). We found no difference in the mAS across tumors with a PD-L1 tumor proportion score of ≥50%, 1-49%, or < 1% (mAS 5 vs 7 vs 6, respectively, P = 0.26), nor was there any correlation between aneuploidy and TMB when taken as continuous variables (Spearman R: 0.074, P = 0.12). A total of 279 advanced NSCLCs with available aneuploidy scores were treated with ICIs. An URP analysis identified an AS of 2 as the strongest discriminator of objective response to ICI. Compared to pts with an AS > 2 (N = 207, 74.2%), pts with AS ≤2 (N = 72, 25.8%) had a significantly higher objective response rate (ORR 43.0% vs 19.8%, P < 0.001), a significantly longer median progression-free survival (mPFS 6.2 vs 2.9 months, HR: 0.70 [95% CI: 0.52-0.94], P = 0.02), and a significantly longer median overall survival (mOS 19.8 vs 13.8 months, HR: 0.66 [95% CI: 0.47-0.94], P = 0.02) to treatment with ICIs. After adjusting for other variables such as performance status, presence of oncogenic driver mutation, PD-L1, TMB, and line of treatment, AS was significantly associated with improved mPFS (HR: 0.72 [95% CI: 0.52-0.99], P = 0.04) and mOS (HR: 0.64 [95% CI: 0.44-0.94], P = 0.02). By contrast, among pts who received first-line platinum doublet chemotherapy without ICI, an AS ≤2 (N = 29), when compared to an AS > 2 (N = 56), did not correlate with improved ORR (55.2% vs 44.6%, P = 0.4) or PFS (5.3 vs 4.8 months, HR 0.83 [95% CI: 0.5-1.3], P = 0.43). Among 179 NSCLCs profiled by multiplex immunofluorescence, compared to cancers with an AS > 2, those with low aneuploidy had significantly higher numbers of CD8+, Foxp3+, PD-1+ immune cells, and PD-1+ CD8+ T cell, both intratumorally and when looking at the total numbers of cells within the tumor and at the tumor-stroma interface. Conclusions: NSCLCs with low aneuploidy have a distinct immune microenvironment and more favorable outcomes to ICIs.

A Randomized Trial of Combined PD-L1 and CTLA-4 Inhibition with Targeted Low-Dose or Hypofractionated Radiation for Patients with Metastatic Colorectal Cancer

PURPOSE

Prospective human data are lacking regarding safety, efficacy, and immunologic impacts of different radiation doses administered with combined PD-L1/CTLA-4 blockade.

PATIENTS AND METHODS

We performed a multicenter phase II study randomly assigning patients with metastatic microsatellite stable colorectal cancer to repeated low-dose fractionated radiation (LDFRT) or hypofractionated radiation (HFRT) with PD-L1/CTLA-4 inhibition. The primary endpoint was response outside the radiation field. Correlative samples were analyzed using multiplex immunofluorescence (IF), IHC, RNA/T-cell receptor (TCR) sequencing, cytometry by time-of-flight (CyTOF), and Olink.

RESULTS

Eighteen patients were evaluable for response. Median lines of prior therapy were four (range, 1-7). Sixteen patients demonstrated toxicity potentially related to treatment (84%), and 8 patients had grade 3-4 toxicity (42%). Best response was stable disease in 1 patient with out-of-field tumor shrinkage. Median overall survival was 3.8 months (90% confidence interval, 2.3-5.7 months). Correlative IF and RNA sequencing (RNA-seq) revealed increased infiltration of CD8⁺ and CD8⁺/PD-1⁺/Ki-67⁺ T cells in the radiation field after HFRT. LDFRT increased foci of micronuclei/primary nuclear rupture in two subjects. CyTOF and RNA-seq demonstrated significant declines in multiple circulating immune populations, particularly in patients receiving HFRT. TCR sequencing revealed treatment-associated changes in T-cell repertoire in the tumor and peripheral blood.

CONCLUSIONS

We demonstrate the feasibility and safety of adding LDFRT and HFRT to PD-L1/CTLA-4 blockade. Although the best response of stable disease does not support the use of concurrent PD-L1/CTLA-4 inhibition with HFRT or LDFRT in this population, biomarkers provide support that both LDFRT and HFRT impact the local immune microenvironment and systemic immunogenicity that can help guide future studies.